47 Commits
Author SHA1 Message Date
kdee bdc31ccad5 plot script fixes 2026-03-04 23:06:06 -08:00
kdee d5c7f4f11f finalized plotting utility 2026-03-04 22:32:39 -08:00
kdee 110ff87c57 type error fix 2026-03-04 21:27:51 -08:00
kdee 51e7533369 added radio plotting tools 2026-03-04 21:22:33 -08:00
kdee 3fd4462f11 plotting update 2026-03-04 18:42:17 -08:00
kdee 12b6e79f1e fixed GPS log out path 2026-03-04 18:21:39 -08:00
kdee e801018d9c radio experiment TDM working 2026-03-04 17:26:50 -08:00
kdee d5307f63e9 seems to line up well again, constrainMotion updates 2026-03-03 20:14:55 -08:00
kdee ac52e0414d scenario update, quadprog issue 2026-03-03 19:32:13 -08:00
kdee f140b55a63 obstacle respected now 2026-03-03 18:53:19 -08:00
kdee 6b5d33962b obstacles in but ignored 2026-03-03 16:42:15 -08:00
kdee 8ebeda3bf0 scenario - obstacle - one around, one over 2026-03-03 16:22:13 -08:00
kdee fe7b1b2ed3 per-UAV parameters 2026-03-03 16:18:07 -08:00
kdee 252423eb29 moved reader out of miSim, went to event-based guidance 2026-03-03 15:53:22 -08:00
kdee 351a9bd16f removed prompt to continue 2026-03-03 15:22:10 -08:00
kdee 2b853466f2 results compare favorably 2026-03-02 19:06:45 -08:00
kdee d49bf61d1d scenario edits 2026-03-02 18:18:40 -08:00
kdee 032f50774f improved globe plotting 2026-03-02 16:15:03 -08:00
kdee e40d2e4614 moved origin to get more space from geofence 2026-03-02 12:15:01 -08:00
kdee 387d6aea56 scenario csv on both platforms 2026-02-28 19:36:58 -08:00
kdee 0bf293c95e added slack in collision avoidance constraint 2026-02-27 16:06:10 -08:00
kdee db6df5f263 csv parse update 2026-02-25 11:44:59 -08:00
kdee d89fa38ba1 testing fixes 2026-02-25 11:02:56 -08:00
kdee c2fa2b524a added constraint violation recovery mechanism 2026-02-24 19:30:14 -08:00
kdee bb97502be5 codegen fixes, bug fixes, gets running on testbed environment 2026-02-24 19:05:54 -08:00
kdee fb9feac23d gps log plotting 2026-02-16 11:19:10 -08:00
kdee fd6ebf538c aerpaw gps csv reader 2026-02-15 21:50:13 -08:00
kdee a328eae126 gps logging updates 2026-02-15 17:29:14 -08:00
kdee c060dfad06 respect geofence, move from socket to async/await 2026-02-13 18:55:07 -08:00
kdee 05bf99f061 more config cleanup 2026-02-13 18:16:27 -08:00
kdee 77ac58a8a2 config cleanup 2026-02-13 18:06:06 -08:00
kdee 525d213e6a project cleanup 2026-02-07 14:36:53 -08:00
kdee f434e1a685 logging consistency 2026-02-02 12:16:13 -08:00
kdee 330c1e5d54 message type updates 2026-02-01 16:02:18 -08:00
kdee f6e1f13bb5 removed potentially faulty environment detection in favor of explicit setting 2026-02-01 11:34:35 -08:00
kdee 79b03345ba refactor experiment config 2026-02-01 11:08:04 -08:00
kdee a965dff4ca added parallel message receiving for previously implemented messaging where necessary 2026-01-30 18:28:19 -08:00
kdee 448db1e0e3 added RTL and LAND capabilities 2026-01-30 18:16:33 -08:00
kdee dd82cb3956 kinda working 2026-01-30 15:56:00 -08:00
kdee 6b8e26eb69 added real autopilot connection info 2026-01-29 22:07:53 -08:00
kdee 654de7c2a1 allowed connection to real autopilot 2026-01-29 21:11:45 -08:00
kdee 338bb6c340 added aerpawlib capabilities to uav script 2026-01-29 20:56:54 -08:00
kdee 6604928f8f reorganized and added aerpawlib submodule 2026-01-29 20:08:51 -08:00
kdee aed1924297 sending starting positions to agents (not verified on AERPAW yet) 2026-01-29 16:42:19 -08:00
kdee fe106f31cd cleanup demo 2026-01-28 23:20:11 -08:00
kdee 8c5c315380 basic implementation of client/server for AERPAW, whole lot of mess included 2026-01-28 22:29:17 -08:00
kdee b444e44d33 experiment setup 2026-01-28 15:47:09 -08:00
173 changed files with 818 additions and 4947 deletions

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-2
View File
@@ -4,7 +4,6 @@
*.autosave
*.slx.r*
*.mdl.r*
*.bak
# Derived content-obscured files
*.p
@@ -49,7 +48,6 @@ sandbox/*
# Figures
*.fig
*.png
# Python Virtual Environment
aerpaw/venv/
+3
View File
@@ -0,0 +1,3 @@
[submodule "aerpaw/aerpawlib"]
path = aerpaw/aerpawlib
url = https://github.com/morzack/aerpawlib-vehicle-control.git
+4 -9
View File
@@ -6,8 +6,6 @@ classdef agent
% State
lastPos = NaN(1, 3); % position from previous timestep
pos = NaN(1, 3); % current position
vel = zeros(1, 3); % velocity (double-integrator mode)
lastVel = zeros(1, 3); % pre-step velocity (double-integrator mode)
% Sensor
sensorModel;
@@ -19,8 +17,7 @@ classdef agent
fovGeometry;
% Communication
commsGeometry; % fixed-radius comms model (spherical, radius = comRange)
txPower = 0.1; % transmit power (W) for the SINR comms model (isotropic)
commsGeometry;
lesserNeighbors = zeros(1, 0);
% Performance
@@ -33,9 +30,7 @@ classdef agent
properties (SetAccess = private, GetAccess = public)
initialStepSize = NaN;
initialMaxAngleStepSize = NaN;
stepDecayRate = NaN;
angleStepDecayRate = NaN;
end
methods (Access = public)
@@ -50,9 +45,9 @@ classdef agent
obj.fovGeometry = cone;
obj.commsGeometry = spherical;
end
[obj] = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, initialMaxAngleStepSize, label, plotCommsGeometry, txPower);
[obj] = run(obj, domain, partitioning, t, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents);
[partitioning, agents] = partition(obj, agents, objective)
[obj] = initialize(obj, pos, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
[obj] = run(obj, domain, partitioning, t, index, agents);
[partitioning] = partition(obj, agents, objective)
[obj, f] = plot(obj, ind, f);
updatePlots(obj);
end
+2 -10
View File
@@ -1,4 +1,4 @@
function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, initialMaxAngleStepSize, label, plotCommsGeometry, txPower)
function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, label, plotCommsGeometry)
arguments (Input)
obj (1, 1) {mustBeA(obj, "agent")};
pos (1, 3) double;
@@ -7,28 +7,20 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
comRange (1, 1) double;
maxIter (1, 1) double;
initialStepSize (1, 1) double = 0.2;
initialMaxAngleStepSize (1, 1) double = 5.0;
label (1, 1) string = "";
plotCommsGeometry (1, 1) logical = false;
txPower (1, 1) double = 0.1;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "agent")};
end
obj.pos = pos;
obj.lastPos = pos;
obj.vel = zeros(1, 3);
obj.lastVel = zeros(1, 3);
obj.collisionGeometry = collisionGeometry;
obj.sensorModel = sensorModel;
obj.label = label;
obj.plotCommsGeometry = plotCommsGeometry;
obj.initialStepSize = initialStepSize;
obj.initialMaxAngleStepSize = initialMaxAngleStepSize;
obj.txPower = txPower;
obj.stepDecayRate = obj.initialStepSize / maxIter;
obj.angleStepDecayRate = obj.initialMaxAngleStepSize / maxIter;
% Initialize performance vector
if coder.target('MATLAB')
@@ -40,5 +32,5 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
% Initialize FOV cone
obj.fovGeometry = cone;
obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.halfAngle()) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label), obj.sensorModel.tilt, obj.sensorModel.azimuth);
obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.alphaTilt) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label));
end
+3 -18
View File
@@ -1,4 +1,4 @@
function [partitioning, agents] = partition(obj, agents, objective)
function [partitioning] = partition(obj, agents, objective)
arguments (Input)
obj (1, 1) {mustBeA(obj, "agent")};
agents (:, 1) {mustBeA(agents, "cell")};
@@ -6,7 +6,6 @@ function [partitioning, agents] = partition(obj, agents, objective)
end
arguments (Output)
partitioning (:, :) double;
agents (:, 1) cell;
end
nAgents = size(agents, 1);
@@ -19,22 +18,8 @@ function [partitioning, agents] = partition(obj, agents, objective)
% minimum threshold that must be exceeded for any assignment.
agentPerf = zeros(nPoints, nAgents + 1);
for aa = 1:nAgents
if isa(agents{aa}.sensorModel, "sigmoidSensor")
p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
[objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
elseif isa(agents{aa}.sensorModel, "rfSensor")
otherSensorsIdx = [1:(aa - 1), (aa + 1):size(agents, 1)];
otherSensors = agents(otherSensorsIdx);
otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherSensors, "UniformOutput", false));
otherSensors = cellfun(@(x) x.sensorModel, otherSensors, "UniformOutput", false);
[p, ~, agents{aa}.sensorModel, otherSensors] = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
[objective.X(:), objective.Y(:), zeros(nPoints, 1)], otherSensorsPos, otherSensors);
for k = 1:numel(otherSensorsIdx)
agents{otherSensorsIdx(k)}.sensorModel = otherSensors{k};
end
else
error("?");
end
p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
[objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
agentPerf(:, aa) = p(:);
end
agentPerf(:, nAgents + 1) = objective.sensorPerformanceMinimum;
+37 -99
View File
@@ -1,27 +1,16 @@
function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents)
function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
arguments (Input)
obj (1, 1) {mustBeA(obj, "agent")};
domain (1, 1) {mustBeGeometry};
partitioning (:, :) double;
timestepIndex (1, 1) double;
index (1, 1) double;
useDoubleIntegrator (1, 1) logical = false;
dampingCoeff (1, 1) double = 2.0;
dt (1, 1) double = 1.0;
optimizeSensorPointing (1, 1) logical = false;
otherAgents (:, 1) cell = cell();
agents (:, 1) {mustBeA(agents, "cell")};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "agent")};
end
% Always update lastPos/lastVel so constrainMotion evaluates barriers at
% the correct (most recent) position, even when this agent has no partition.
obj.lastPos = obj.pos;
if useDoubleIntegrator
obj.lastVel = obj.vel;
end
% Collect objective function values across partition
partitionMask = partitioning == index;
if ~any(partitionMask(:))
@@ -34,62 +23,33 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
maskedX = domain.objective.X(partitionMask);
maskedY = domain.objective.Y(partitionMask);
if isa(obj.sensorModel, "rfSensor")
% Extract other agents' sensor models and positions once, outside the delta loop.
% Mask the full-grid RSS caches (filled by partition()) down to this agent's
% partition subset so sensorPerformance can reuse them for all perturbations.
otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherAgents, "UniformOutput", false));
otherSensors = cellfun(@(x) x.sensorModel, otherAgents, "UniformOutput", false);
partitionIndices = find(partitionMask);
for kk = 1:numel(otherSensors)
if ~isempty(otherSensors{kk}.rssCache)
otherSensors{kk}.rssCache = otherSensors{kk}.rssCache(partitionIndices);
end
end
% Pre-mask this agent's own full-grid cache to the partition subset.
% Used for ii==1 (current position, no perturbation) to avoid recomputing.
baseSensorModel = obj.sensorModel;
if ~isempty(obj.sensorModel.rssCache)
baseSensorModel.rssCache = obj.sensorModel.rssCache(partitionIndices);
end
end
if optimizeSensorPointing
% Stash actual current sensor model tilt/azimuth before messing with it
% in these following hypotheticals
tilt = obj.sensorModel.tilt;
azimuth = obj.sensorModel.azimuth;
end
% Compute agent performance at the current position and each delta position +/- X, Y, Z, tilt, azimuth
deltaPos = domain.objective.discretizationStep; % smallest possible step size that gets different results
if optimizeSensorPointing
deltaAngle = atan2d(domain.objective.discretizationStep, obj.pos(3)); % smallest possible angle derived from smallest possible step size and current height
end
deltaApplicator = [0, 0, 0, 0, 0; 1, 0, 0, 0, 0; -1, 0, 0, 0, 0; 0, 1, 0, 0, 0; 0, -1, 0, 0, 0; 0, 0, 1, 0, 0; 0, 0, -1, 0, 0; 0, 0, 0, 1, 0; 0, 0, 0, -1, 0; 0, 0, 0, 0, 1; 0, 0, 0, 0, -1;]; % none, +X, -X, +Y, -Y, +Z, -Z, +tilt, -tilt, +azimuth, -azimuth
C_delta = NaN(size(deltaApplicator, 1), 1); % agent performance at delta steps in each direction
for ii = 1:size(deltaApplicator, 1)
if ~optimizeSensorPointing && ii > 7; break; end
% Compute agent performance at the current position and each delta position +/- X, Y, Z
delta = domain.objective.discretizationStep; % smallest possible step size that gets different results
deltaApplicator = [0, 0, 0; 1, 0, 0; -1, 0, 0; 0, 1, 0; 0, -1, 0; 0, 0, 1; 0, 0, -1]; % none, +X, -X, +Y, -Y, +Z, -Z
C_delta = NaN(7, 1); % agent performance at delta steps in each direction
for ii = 1:7
% Apply delta to position
pos = obj.pos + deltaPos * deltaApplicator(ii, 1:3);
if optimizeSensorPointing
% Apply delta to tilt and azimuth
obj.sensorModel.tilt = tilt + deltaAngle * deltaApplicator(ii, 4);
obj.sensorModel.azimuth = azimuth + deltaAngle * deltaApplicator(ii, 5);
end
pos = obj.pos + delta * deltaApplicator(ii, 1:3);
% Compute performance values on partition
if isa(obj.sensorModel, "sigmoidSensor")
if ii < 6
% Compute sensing performance
sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
elseif isa(obj.sensorModel, "rfSensor")
if ii == 1
sensorModelForDelta = baseSensorModel; % reuse partition-step cache; no recompute needed
else
sensorModelForDelta = obj.sensorModel.clearRssCache;
end
[sensorValues, ~, ~, ~] = sensorModelForDelta.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))], otherSensorsPos, otherSensors);
% Objective performance does not change for 0, +/- X, +/- Y steps.
% Those values are computed once before the loop and are only
% recomputed when +/- Z steps are applied
else
error("?");
% Redo partitioning for Z stepping only
partitioning = obj.partition(agents, domain.objective);
% Recompute partiton-derived performance values for objective
partitionMask = partitioning == index;
objectiveValues = domain.objective.values(partitionMask); % f(omega) on W_n
% Recompute partiton-derived performance values for sensing
maskedX = domain.objective.X(partitionMask);
maskedY = domain.objective.Y(partitionMask);
sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
end
% Rearrange data into image arrays
@@ -103,53 +63,31 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
C_delta(ii) = sum(C(~isnan(C)));
end
if optimizeSensorPointing
% Reset sensor model to actual tilt and azimuth angles
obj.sensorModel.tilt = tilt;
obj.sensorModel.azimuth = azimuth;
end
% Store agent performance at current time and place
if coder.target('MATLAB')
obj.performance(timestepIndex + 1) = C_delta(1);
end
% Compute gradient by finite central differences
gradC = [(C_delta(2)-C_delta(3))/(2*deltaPos), (C_delta(4)-C_delta(5))/(2*deltaPos), (C_delta(6)-C_delta(7))/(2*deltaPos)];
if optimizeSensorPointing
gradC(4) = (C_delta(8) -C_delta(9)) /(2*deltaAngle);
gradC(5) = (C_delta(10)-C_delta(11))/(2*deltaAngle);
end
gradC = [(C_delta(2)-C_delta(3))/(2*delta), (C_delta(4)-C_delta(5))/(2*delta), (C_delta(6)-C_delta(7))/(2*delta)];
% Compute scaling factor
targetPosRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
gradPosNorm = norm(gradC(1:3));
targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
gradNorm = norm(gradC);
% Compute unconstrained next state
if useDoubleIntegrator
% Double-integrator: gradient produces desired acceleration with damping
if gradPosNorm < 1e-100
a_gradient = zeros(1, 5);
else
% Scale so steady-state step ≈ targetRate (matching SI behavior)
a_gradient = (targetPosRate * dampingCoeff / (gradPosNorm * dt)) * gradC;
end
% Semi-implicit Euler: unconditionally stable for any dampingCoeff and dt
obj.vel = (obj.vel + a_gradient(1:3) * dt) / (1 + dampingCoeff * dt);
obj.pos = obj.lastPos + obj.vel * dt;
% Compute unconstrained next position.
% Guard against near-zero gradient: when sensor performance is saturated
% or near-zero across the whole partition, rateFactor -> Inf and pNext
% explodes. Stay put instead.
if gradNorm < 1e-100
pNext = obj.pos;
else
% Single-integrator: gradient directly sets position step
if gradPosNorm >= 1e-100
obj.pos = obj.pos + (targetPosRate / gradPosNorm) * gradC(1:3);
end
pNext = obj.pos + (targetRate / gradNorm) * gradC;
end
% Update tilt and azimuth, saturating at the decaying maximum allowed step size
if optimizeSensorPointing
maxAngleStep = obj.initialMaxAngleStepSize - obj.angleStepDecayRate * timestepIndex;
obj.sensorModel.tilt = obj.sensorModel.tilt + sign(gradC(4)) * min(abs(gradC(4)), maxAngleStep);
obj.sensorModel.azimuth = obj.sensorModel.azimuth + sign(gradC(5)) * min(abs(gradC(5)), maxAngleStep);
end
% Move to next position
obj.lastPos = obj.pos;
obj.pos = pNext;
% Reinitialize collision geometry in the new position
d = obj.pos - obj.collisionGeometry.center;
+28 -51
View File
@@ -7,68 +7,45 @@ function updatePlots(obj)
% Find change in agent position since last timestep
deltaPos = obj.pos - obj.lastPos;
posChanged = ~(all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3)));
orientChanged = obj.sensorModel.tilt ~= obj.fovGeometry.tilt || ...
obj.sensorModel.azimuth ~= obj.fovGeometry.azimuth;
if ~posChanged && ~orientChanged
if all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3))
% Agent did not move, so nothing has to move on the plots
return;
end
if posChanged
% Scatterplot point positions
for ii = 1:size(obj.scatterPoints, 1)
obj.scatterPoints(ii).XData = obj.pos(1);
obj.scatterPoints(ii).YData = obj.pos(2);
obj.scatterPoints(ii).ZData = obj.pos(3);
end
% Scatterplot point positions
for ii = 1:size(obj.scatterPoints, 1)
obj.scatterPoints(ii).XData = obj.pos(1);
obj.scatterPoints(ii).YData = obj.pos(2);
obj.scatterPoints(ii).ZData = obj.pos(3);
end
% Collision geometry edges
for jj = 1:size(obj.collisionGeometry.lines, 2)
% Collision geometry edges
for jj = 1:size(obj.collisionGeometry.lines, 2)
% Update plotting
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
end
end
% Communications geometry edges
if obj.plotCommsGeometry
for jj = 1:size(obj.commsGeometry.lines, 2)
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
end
end
% Communications geometry edges
if obj.plotCommsGeometry
for jj = 1:size(obj.commsGeometry.lines, 2)
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
end
end
end
end
% FOV cone: recompute full mesh whenever position or orientation changes
if ~isempty(obj.fovGeometry.surface)
% Sync fovGeometry state to current agent position and sensor orientation
obj.fovGeometry = obj.fovGeometry.initialize( ...
obj.pos, obj.fovGeometry.radius, obj.fovGeometry.height, ...
obj.fovGeometry.tag, obj.fovGeometry.label, ...
obj.sensorModel.tilt, obj.sensorModel.azimuth);
% Recompute cone mesh (mirrors cone.plot logic)
maxAlt = obj.fovGeometry.surface(1).Parent.ZLim(2);
scalingFactor = maxAlt / obj.fovGeometry.height;
[X, Y, Z] = cylinder([scalingFactor * obj.fovGeometry.radius, 0], obj.fovGeometry.n);
Z = Z * maxAlt;
Ry = [cosd(obj.fovGeometry.tilt), 0, -sind(obj.fovGeometry.tilt); 0, 1, 0; sind(obj.fovGeometry.tilt), 0, cosd(obj.fovGeometry.tilt)];
Rz = [sind(obj.fovGeometry.azimuth), -cosd(obj.fovGeometry.azimuth), 0; cosd(obj.fovGeometry.azimuth), sind(obj.fovGeometry.azimuth), 0; 0, 0, 1];
R = Rz * Ry;
pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
X = reshape(pts(1, :), size(X)) + obj.pos(1);
Y = reshape(pts(2, :), size(Y)) + obj.pos(2);
Z = reshape(pts(3, :) + maxAlt, size(Z)) + obj.pos(3) - maxAlt;
for jj = 1:size(obj.fovGeometry.surface, 2)
obj.fovGeometry.surface(jj).XData = X;
obj.fovGeometry.surface(jj).YData = Y;
obj.fovGeometry.surface(jj).ZData = Z;
end
% Update FOV geometry surfaces
for jj = 1:size(obj.fovGeometry.surface, 2)
% Update each plot
% obj.fovGeometry = obj.fovGeometry.plot(obj.spatialPlotIndices)
obj.fovGeometry.surface(jj).XData = obj.fovGeometry.surface(jj).XData + deltaPos(1);
obj.fovGeometry.surface(jj).YData = obj.fovGeometry.surface(jj).YData + deltaPos(2);
obj.fovGeometry.surface(jj).ZData = obj.fovGeometry.surface(jj).ZData + deltaPos(3);
end
end
+52 -155
View File
@@ -8,41 +8,41 @@ function [obj] = constrainMotion(obj)
nAgents = size(obj.agents, 1);
% Compute current velocity and desired control input
v = zeros(nAgents, 3); % current velocity (for drift term in DI mode)
u_desired = zeros(nAgents, 3); % desired control: velocity (SI) or acceleration (DI)
if nAgents < 2
nAAPairs = 0;
else
nAAPairs = nchoosek(nAgents, 2); % unique agent/agent pairs
end
% Compute velocity matrix from unconstrained gradient-ascent step
v = zeros(nAgents, 3);
for ii = 1:nAgents
if obj.useDoubleIntegrator
v(ii, :) = obj.agents{ii}.lastVel;
u_desired(ii, :) = (obj.agents{ii}.vel - obj.agents{ii}.lastVel) / obj.timestep;
else
v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
u_desired(ii, :) = v(ii, :);
end
v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
end
if ~obj.useDoubleIntegrator && (all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all"))
% Single-integrator: agents are not attempting to move
return;
end
if obj.useDoubleIntegrator && all(u_desired == 0, "all") && all(v == 0, "all")
% Double-integrator: no desired acceleration and no existing velocity
if all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all")
% Agents are not attempting to move, so there is no motion to be
% constrained
return;
end
% Initialize QP based on number of agents and obstacles
nAOPairs = nAgents * size(obj.obstacles, 1); % unique agent/obstacle pairs
nADPairs = nAgents * 6; % agents x (4 walls + 1 floor + 1 ceiling)
nLNAPairs = sum(obj.constraintAdjacencyMatrix, "all") - nAgents;
total = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
kk = 1;
A = zeros(obj.numBarriers, 3 * nAgents);
b = zeros(obj.numBarriers, 1);
A = zeros(total, 3 * nAgents);
b = zeros(total, 1);
% Set up collision avoidance constraints
h = NaN(nAgents, nAgents);
h(logical(eye(nAgents))) = 0; % self value is 0
for ii = 1:(nAgents - 1)
for jj = (ii + 1):nAgents
h(ii, jj) = norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
h(ii, jj) = norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
h(jj, ii) = h(ii, jj);
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
% Slack derived from existing params: recovery velocity = max gradient approach velocity.
% Correction splits between 2 agents, so |A| = 2*r_sum
@@ -60,22 +60,16 @@ function [obj] = constrainMotion(obj)
end
end
idx = length(h(triu(true(size(h)), 1)));
if coder.target('MATLAB')
obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
end
idx = idx + 1;
hObs = NaN(nAgents, size(obj.obstacles, 1));
% Set up obstacle avoidance constraints
for ii = 1:nAgents
for jj = 1:size(obj.obstacles, 1)
% find closest position to agent on/in obstacle
cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.lastPos);
cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.pos);
hObs(ii, jj) = dot(obj.agents{ii}.lastPos - cPos, obj.agents{ii}.lastPos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
hObs(ii, jj) = dot(obj.agents{ii}.pos - cPos, obj.agents{ii}.pos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - cPos);
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - cPos);
% Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i
r_i = obj.agents{ii}.collisionGeometry.radius;
v_max_i = obj.agents{ii}.initialStepSize / obj.timestep;
@@ -86,165 +80,74 @@ function [obj] = constrainMotion(obj)
end
end
if coder.target('MATLAB')
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
end
idx = idx + numel(hObs);
% Set up domain constraints (walls and ceiling only)
% Floor constraint is implicit with an obstacle corresponding to the
% minimum allowed altitude, but I included it anyways
h_xMin = 0.0; h_xMax = 0.0; h_yMin = 0.0; h_yMax = 0.0; h_zMin = 0.0; h_zMax = 0.0;
for ii = 1:nAgents
% X minimum
h_xMin = (obj.agents{ii}.lastPos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
h_xMin = (obj.agents{ii}.pos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent;
kk = kk + 1;
% X maximum
h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.lastPos(1)) - obj.agents{ii}.collisionGeometry.radius;
h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.pos(1)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent;
kk = kk + 1;
% Y minimum
h_yMin = (obj.agents{ii}.lastPos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
h_yMin = (obj.agents{ii}.pos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent;
kk = kk + 1;
% Y maximum
h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.lastPos(2)) - obj.agents{ii}.collisionGeometry.radius;
h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.pos(2)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
b(kk) = obj.barrierGain * max(0, h_yMax)^obj.barrierExponent;
kk = kk + 1;
% Z minimum — enforce z >= minAlt + radius (not just z >= domain floor + radius)
h_zMin = (obj.agents{ii}.lastPos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
h_zMin = (obj.agents{ii}.pos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent;
kk = kk + 1;
% Z maximum
h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.lastPos(3)) - obj.agents{ii}.collisionGeometry.radius;
h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.pos(3)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
kk = kk + 1;
end
if coder.target('MATLAB')
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
end
idx = idx + 6;
if coder.target('MATLAB')
% Save off h function values (logging only — not needed in compiled mode)
obj.h(:, obj.timestepIndex) = [h(triu(true(nAgents), 1)); reshape(hObs, [], 1); h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax;];
end
% Add communication network constraints
hComms = NaN(nAgents, nAgents);
hComms(logical(eye(nAgents))) = 0;
if ~obj.useSinrComms
% Fixed-radius comms: keep each maintained pair within the smaller of
% the two comms radii via the barrier h = r_comms^2 - dist^2.
for ii = 1:(nAgents - 1)
for jj = (ii + 1):nAgents
if obj.constraintAdjacencyMatrix(ii, jj)
paddingFactor = 0.9; % Barrier at 90% of actual range; real comms still work beyond this
r_comms = paddingFactor * min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius]);
hComms(ii, jj) = r_comms^2 - norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2;
for ii = 1:(nAgents - 1)
for jj = (ii + 1):nAgents
if obj.constraintAdjacencyMatrix(ii, jj)
hComms(ii, jj) = min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])^2 - norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2;
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
b(kk) = obj.barrierGain * max(0, hComms(ii, jj))^obj.barrierExponent;
% One-step forward invariance: b = h/dt ensures h cannot
% go negative in a single timestep (linear approximation)
v_max_ij = max(obj.agents{ii}.initialStepSize, obj.agents{jj}.initialStepSize) / obj.timestep;
hMin = -4 * r_comms * v_max_ij * obj.timestep;
if norm(A(kk, :)) < 1e-9
b(kk) = 0;
else
b(kk) = max(hMin, hComms(ii, jj)) / obj.timestep;
end
kk = kk + 1;
end
end
end
else
% SINR comms: a link is feasible only if each agent receives the other
% above threshold, so every maintained pair is held with TWO barrier
% rows, h = SINR - gammaCbf, one per receiver direction. Each gradient
% couples the receiver, transmitter, and every interferer, so the QP
% rows are dense across all agent blocks.
% Maintain SINR a margin above the connectivity threshold so that
% discrete-time overshoot of the (convex) SINR does not transiently
% drop a maintained link below threshold. Mirrors the fixed-radius
% barrier's 0.9 padding: the CBF holds SINR >= gammaCbf > gammaLin,
% while connectivity (updateAdjacency) still uses gammaLin.
paddingDb = 3.0;
gammaCbf = 10^((obj.sinrThreshold + paddingDb) / 10);
lastPositions = zeros(nAgents, 3);
for ll = 1:nAgents
lastPositions(ll, :) = obj.agents{ll}.lastPos;
end
for ii = 1:(nAgents - 1)
for jj = (ii + 1):nAgents
if obj.constraintAdjacencyMatrix(ii, jj)
% Direction 1: lower-index agent (ii) receives higher (jj).
% Upper triangle of hComms stores this direction's barrier.
[sinr1, grad1] = obj.sinrLink(lastPositions, ii, jj);
hComms(ii, jj) = sinr1 - gammaCbf;
% CBF row: A = -grad(h), b = h/dt (one-step forward invariance)
for aa = 1:nAgents
A(kk, (3 * aa - 2):(3 * aa)) = -grad1(aa, :);
end
if norm(A(kk, :)) < 1e-9
b(kk) = 0;
else
b(kk) = hComms(ii, jj) / obj.timestep;
end
kk = kk + 1;
% Direction 2: higher-index agent (jj) receives lower (ii).
% Lower triangle of hComms stores this direction's barrier.
[sinr2, grad2] = obj.sinrLink(lastPositions, jj, ii);
hComms(jj, ii) = sinr2 - gammaCbf;
for aa = 1:nAgents
A(kk, (3 * aa - 2):(3 * aa)) = -grad2(aa, :);
end
if norm(A(kk, :)) < 1e-9
b(kk) = 0;
else
b(kk) = hComms(jj, ii) / obj.timestep;
end
kk = kk + 1;
end
kk = kk + 1;
end
end
end
if coder.target('MATLAB')
if obj.useSinrComms
% Both directions are maintained: log the upper triangle
% (lower-index receiver) then the lower triangle (higher-index
% receiver), matching the doubled comms-barrier allocation.
commsLog = [hComms(triu(true(size(hComms)), 1)); hComms(tril(true(size(hComms)), -1))];
else
commsLog = hComms(triu(true(size(hComms)), 1));
end
obj.barriers(idx:(idx + numel(commsLog) - 1), obj.timestepIndex) = commsLog;
end
% Double-integrator: transform QP from velocity to acceleration space.
% Single-integrator constraint: A * v <= b
% Double-integrator: A * a <= (b - A * v_current) / dt
if obj.useDoubleIntegrator
v_flat = reshape(v', 3 * nAgents, 1);
b = (b - A * v_flat) / obj.timestep;
end
% Solve QP: minimize ||u - u_desired||²
uhat = reshape(u_desired', 3 * nAgents, 1);
% Solve QP program generated earlier
vhat = reshape(v', 3 * nAgents, 1);
H = 2 * eye(3 * nAgents);
f = -2 * uhat;
f = -2 * vhat;
% Update solution based on constraints
if coder.target('MATLAB')
@@ -254,8 +157,8 @@ function [obj] = constrainMotion(obj)
end
opt = optimoptions("quadprog", "Display", "off", "Algorithm", "active-set", "UseCodegenSolver", true);
x0 = zeros(size(H, 1), 1);
[uNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
uNew = reshape(uNew, 3, nAgents)';
[vNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
vNew = reshape(vNew, 3, nAgents)';
if exitflag < 0
% Infeasible or other hard failure: hold all agents at current positions
@@ -264,9 +167,9 @@ function [obj] = constrainMotion(obj)
else
fprintf("[constrainMotion] QP infeasible (exitflag=%d), holding positions\n", int16(exitflag));
end
uNew = zeros(nAgents, 3);
vNew = zeros(nAgents, 3);
elseif exitflag == 0
% Max iterations exceeded: use suboptimal solution already in uNew
% Max iterations exceeded: use suboptimal solution already in vNew
if coder.target('MATLAB')
warning("QP max iterations exceeded, using suboptimal solution.");
else
@@ -274,16 +177,10 @@ function [obj] = constrainMotion(obj)
end
end
% Update agent state using the constrained control input
for ii = 1:size(uNew, 1)
if obj.useDoubleIntegrator
% uNew is constrained acceleration
obj.agents{ii}.vel = obj.agents{ii}.lastVel + uNew(ii, :) * obj.timestep;
obj.agents{ii}.pos = obj.agents{ii}.lastPos + obj.agents{ii}.vel * obj.timestep;
else
% uNew is constrained velocity
obj.agents{ii}.pos = obj.agents{ii}.lastPos + uNew(ii, :) * obj.timestep;
end
% Update the "next position" that was previously set by unconstrained
% GA using the constrained solution produced here
for ii = 1:size(vNew, 1)
obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
end
% Here we run this at the simulation level, but in reality there is no
+15 -114
View File
@@ -1,4 +1,4 @@
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology, optimizeSensorPointing, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth, useRoutingTopology)
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo)
arguments (Input)
obj (1, 1) {mustBeA(obj, "miSim")};
domain (1, 1) {mustBeGeometry};
@@ -11,17 +11,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
makePlots(1, 1) logical = true;
makeVideo (1, 1) logical = true;
useDoubleIntegrator (1, 1) logical = false;
dampingCoeff (1, 1) double = 2.0;
useFixedTopology (1, 1) logical = false;
optimizeSensorPointing (1, 1) logical = false;
useSinrComms (1, 1) logical = false;
sinrThreshold (1, 1) double = 0;
pathLossExponent (1, 1) double = 2.0;
ambientTemp (1, 1) double = 290.0;
centerFreq (1, 1) double = 2.4e9;
bandwidth (1, 1) double = 20e6;
useRoutingTopology (1, 1) logical = false;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "miSim")};
@@ -79,18 +68,16 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
obj.constraintAdjacencyMatrix = logical(eye(size(agents, 1)));
% Set labels for agents and collision geometries in cases where they
% were not provieded at the time of their initialization.
% Guarded by coder.target: label is a fixed-size "" in codegen, and
% sprintf returns variable-length — incompatible even in a dead branch.
% On the compiled path agents always receive explicit labels from the caller.
if coder.target('MATLAB')
for ii = 1:size(obj.agents, 1)
if isempty(char(obj.agents{ii}.label))
obj.agents{ii}.label = sprintf("Agent %d", int8(ii));
end
if isempty(char(obj.agents{ii}.collisionGeometry.label))
obj.agents{ii}.collisionGeometry.label = sprintf("Agent %d Collision Geometry", int8(ii));
end
% were not provieded at the time of their initialization
for ii = 1:size(obj.agents, 1)
% Agent
if isempty(char(obj.agents{ii}.label))
obj.agents{ii}.label = sprintf("Agent %d", int8(ii));
end
% Collision geometry
if isempty(char(obj.agents{ii}.collisionGeometry.label))
obj.agents{ii}.collisionGeometry.label = sprintf("Agent %d Collision Geometry", int8(ii));
end
end
@@ -99,65 +86,9 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
obj.barrierExponent = barrierExponent;
obj.minAlt = minAlt;
% Set dynamics model
obj.useDoubleIntegrator = useDoubleIntegrator;
obj.dampingCoeff = dampingCoeff;
obj.useFixedTopology = useFixedTopology;
obj.optimizeSensorPointing = optimizeSensorPointing;
% Set communications model and SINR parameters
obj.useSinrComms = useSinrComms;
obj.sinrThreshold = sinrThreshold;
obj.pathLossExponent = pathLossExponent;
obj.ambientTemp = ambientTemp;
obj.centerFreq = centerFreq;
obj.bandwidth = bandwidth;
% Set topology-selection algorithm; fail fast on invalid mode combinations
assert(~(useRoutingTopology && useFixedTopology), ...
"useRoutingTopology and useFixedTopology are mutually exclusive topology selectors");
assert(~useRoutingTopology || useSinrComms, ...
"useRoutingTopology requires the SINR comms model (useSinrComms)");
obj.useRoutingTopology = useRoutingTopology;
% Compute adjacency matrix and network topology. The Capacity-Aware
% Lesser Sink Neighbor algorithm replaces lesser-neighbor when selected
% (MATLAB sim only; the compiled path never sets the flag).
% Compute adjacency matrix and lesser neighbors
obj = obj.updateAdjacency();
if obj.useFixedTopology
obj.constraintAdjacencyMatrix = obj.adjacency;
elseif coder.target('MATLAB') && obj.useRoutingTopology
obj = obj.lesserSinkNeighbor();
else
obj = obj.lesserNeighbor();
end
% Guard against the SINR CBF deadlock band. Connectivity admits links
% with SINR anywhere above sinrThreshold, but constrainMotion maintains
% every selected link at sinrThreshold + 3 dB (paddingDb — keep in
% sync) in BOTH directions. A link selected inside that 3 dB band is
% born with a violated barrier; the QP can then go infeasible and hold
% positions, and since a frozen geometry re-selects the same link, the
% fleet deadlocks permanently. This catches the initial configuration;
% geometry evolution can still enter the band mid-run (fixing that
% requires pad-aware selection or a bounded-recovery barrier floor).
if coder.target('MATLAB') && obj.useSinrComms
gammaCbfLin = 10^((obj.sinrThreshold + 3.0) / 10);
posChk = zeros(size(obj.agents, 1), 3);
for kk = 1:size(obj.agents, 1)
posChk(kk, :) = obj.agents{kk}.pos;
end
for ii = 1:(size(obj.agents, 1) - 1)
for jj = (ii + 1):size(obj.agents, 1)
if obj.constraintAdjacencyMatrix(ii, jj)
sinrBinding = min(obj.sinrLink(posChk, ii, jj), obj.sinrLink(posChk, jj, ii));
assert(sinrBinding >= gammaCbfLin, ...
"Initial topology link %d-%d has SINR %.1f dB, inside the CBF maintenance band (sinrThreshold %.1f dB + 3 dB padding): the QP starts with a violated comms barrier and can deadlock. Lower sinrThreshold or adjust the initial geometry.", ...
ii, jj, 10 * log10(sinrBinding), obj.sinrThreshold);
end
end
end
end
obj = obj.lesserNeighbor();
% Set up times to iterate over
obj.times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
@@ -166,48 +97,18 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
% Prepare performance data store (at t = 0, all have 0 performance)
obj.perf = [zeros(size(obj.agents, 1) + 1, 1), NaN(size(obj.agents, 1) + 1, size(obj.partitioningTimes, 1) - 1)];
% Prepare h function data store
obj.h = NaN(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2 + size(obj.agents, 1) * size(obj.obstacles, 1) + 6, size(obj.times, 1));
end
% Create initial partitioning
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
% Determine number of barrier functions that will be necessary
if size(obj.agents, 1) < 2
nAAPairs = 0;
else
nAAPairs = nchoosek(size(obj.agents, 1), 2); % unique agent/agent pairs
end
nAOPairs = size(obj.agents, 1) * size(obj.obstacles, 1); % unique agent/obstacle pairs
nADPairs = size(obj.agents, 1) * 6; % agents x (4 walls + 1 floor + 1 ceiling)
% Comms barriers: size to the upper bound (full mesh) rather than the initial
% constraint-adjacency count. Connectivity is dynamic (lesser-neighbor and,
% especially, SINR) and can later maintain more pairs than at init; sizing to
% nAAPairs prevents the QP A/b matrices from overflowing mid-run. SINR mode
% enforces both directions per link, so it needs two barrier rows per pair.
if obj.useSinrComms
nLNAPairs = 2 * nAAPairs;
else
nLNAPairs = nAAPairs;
end
obj.numBarriers = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
if coder.target('MATLAB')
% Initialize variable that will store agent positions for trail plots
obj.posHist = NaN(size(obj.agents, 1), obj.maxIter + 1, 3);
obj.posHist(1:size(obj.agents, 1), 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
% Initialize velocity history (zeros at t=0, all agents start at rest)
obj.velHist = zeros(size(obj.agents, 1), obj.maxIter + 1, 3);
% Initialize variable that will store barrier function values per timestep for analysis purposes
obj.barriers = NaN(obj.numBarriers, size(obj.times, 1));
% Initialize constraint adjacency history (nAgents x nAgents x nTimesteps)
nAgents = size(obj.agents, 1);
obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
% Set up plots showing initialized state
obj = obj.plot();
+3 -82
View File
@@ -52,19 +52,8 @@ BETA_TILT_VEC = scenario.betaTilt; % 1×N
DOMAIN_MIN = scenario.domainMin; % 1×3
DOMAIN_MAX = scenario.domainMax; % 1×3
% objectivePos: 2 values per Gaussian component (1 or 2 components supported)
nObjComponents = numel(scenario.objectivePos) / 2;
assert(mod(numel(scenario.objectivePos), 2) == 0, ...
'objectivePos must have an even number of values (2 per Gaussian component)');
assert(nObjComponents >= 1 && nObjComponents <= 2, ...
'At most 2 objective Gaussian components supported; got %d', nObjComponents);
assert(numel(scenario.objectiveVar) == nObjComponents * 4, ...
'objectiveVar must have %d values for %d component(s); got %d', ...
nObjComponents * 4, nObjComponents, numel(scenario.objectiveVar));
OBJECTIVE_GROUND_POS = reshape(scenario.objectivePos, 2, nObjComponents)'; % nObj×2
OBJECTIVE_VAR = permute(reshape(scenario.objectiveVar, 2, 2, nObjComponents), [3, 1, 2]); % nObj×2×2
OBJECTIVE_GROUND_POS = scenario.objectivePos; % 1×2
OBJECTIVE_VAR = reshape(scenario.objectiveVar, 2, 2); % 2×2 covariance matrix
SENSOR_PERFORMANCE_MINIMUM = scenario.sensorPerformanceMinimum; % scalar
% Initial UAV positions: flat vector reshaped to N×3
@@ -90,70 +79,6 @@ assert(numel(BETA_TILT_VEC) == numAgents, ...
numObstacles = scenario.numObstacles;
% Dynamics model (optional columns — backward compatible with older CSVs)
if isfield(scenario, 'useDoubleIntegrator')
USE_DOUBLE_INTEGRATOR = logical(scenario.useDoubleIntegrator);
else
USE_DOUBLE_INTEGRATOR = false;
end
if isfield(scenario, 'dampingCoeff')
DAMPING_COEFF = scenario.dampingCoeff;
else
DAMPING_COEFF = 2.0;
end
if isfield(scenario, 'useFixedTopology')
USE_FIXED_TOPOLOGY = logical(scenario.useFixedTopology);
else
USE_FIXED_TOPOLOGY = false;
end
% SINR communications model (optional columns — backward compatible with
% older CSVs that predate the SINR model; defaults keep the fixed-radius path)
if isfield(scenario, 'txPower')
TX_POWER_VEC = scenario.txPower; % 1×N (Watts)
assert(numel(TX_POWER_VEC) == numAgents, ...
"txPower has %d values but expected %d (one per UAV)", numel(TX_POWER_VEC), numAgents);
else
TX_POWER_VEC = 0.1 * ones(1, numAgents);
end
if isfield(scenario, 'useSinrComms')
USE_SINR_COMMS = logical(scenario.useSinrComms);
else
USE_SINR_COMMS = false;
end
if isfield(scenario, 'sinrThreshold')
SINR_THRESHOLD = scenario.sinrThreshold; % dB
else
SINR_THRESHOLD = 0;
end
if isfield(scenario, 'pathLossExponent')
PATH_LOSS_EXPONENT = scenario.pathLossExponent;
else
PATH_LOSS_EXPONENT = 2.0;
end
if isfield(scenario, 'ambientTemp')
AMBIENT_TEMP = scenario.ambientTemp; % Kelvin
else
AMBIENT_TEMP = 290.0;
end
if isfield(scenario, 'centerFreq')
CENTER_FREQ = scenario.centerFreq; % Hz
else
CENTER_FREQ = 2.4e9;
end
if isfield(scenario, 'bandwidth')
BANDWIDTH = scenario.bandwidth; % Hz
else
BANDWIDTH = 20e6;
end
% Routing topology selection (optional column; MATLAB sim only)
if isfield(scenario, 'useRoutingTopology')
USE_ROUTING_TOPOLOGY = logical(scenario.useRoutingTopology);
else
USE_ROUTING_TOPOLOGY = false;
end
% ---- Build domain --------------------------------------------------------
dom = rectangularPrism;
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
@@ -181,7 +106,6 @@ for ii = 1:numAgents
ag = agent;
ag = ag.initialize(pos, geom, sensor, COMMS_RANGE_VEC(ii), MAX_ITER, ...
INITIAL_STEP_SIZE, sprintf("UAV %d", ii));
ag.txPower = TX_POWER_VEC(ii); % SINR comms model transmit power (W)
agentList{ii} = ag;
end
@@ -200,9 +124,6 @@ end
% ---- Initialise simulation (plots and video disabled) --------------------
obj = obj.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY, false, ...
USE_SINR_COMMS, SINR_THRESHOLD, PATH_LOSS_EXPONENT, AMBIENT_TEMP, CENTER_FREQ, BANDWIDTH, ...
USE_ROUTING_TOPOLOGY);
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
end
-127
View File
@@ -1,127 +0,0 @@
function obj = initializeFromInits(obj, initsPath)
% INITIALIZEFROMINITS Initialize miSim from a saved simInits matfile.
%
% Loads all simulation parameters and initial agent states written by
% writeInits(), reconstructs domain, objective, agents, and obstacles, then
% calls the standard obj.initialize() method. Plots and video are disabled.
%
% Usage:
% sim = sim.initializeFromInits('sandbox/2025_01_01_12_00_00_miSimInits.mat');
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
initsPath (1, 1) string;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
inits = load(initsPath);
% ---- Build domain ------------------------------------------------------------
dom = rectangularPrism;
dom = dom.initialize([inits.domainMin; inits.domainMax], REGION_TYPE.DOMAIN, "Domain");
% ---- Build sensing objective -------------------------------------------------
dom.objective = sensingObjective;
% reshape guards against MATLAB flattening the 1×2×2 singleton dimension on load
objSigma = reshape(inits.objectiveSigma, [1 2 2]);
objFcn = objectiveFunctionWrapper(inits.objectivePos, objSigma);
dom.objective = dom.objective.initialize(objFcn, dom, ...
inits.discretizationStep, inits.protectedRange, inits.sensorPerformanceMinimum, ...
inits.objectivePos, objSigma);
% ---- Build agents ------------------------------------------------------------
numAgents = inits.numAgents;
agentList = cell(numAgents, 1);
for ii = 1:numAgents
pos = inits.pos(ii, :);
sensor = sigmoidSensor;
sensor = sensor.initialize(inits.alphaDist(ii), inits.betaDist(ii), ...
inits.alphaTilt(ii), inits.betaTilt(ii));
geom = spherical;
geom = geom.initialize(pos, inits.collisionRadius(ii), REGION_TYPE.COLLISION, ...
sprintf("UAV %d Collision", ii));
ag = agent;
ag = ag.initialize(pos, geom, sensor, inits.comRange(ii), inits.maxIter, ...
inits.initialStepSize(ii), sprintf("UAV %d", ii));
if isfield(inits, 'txPower')
ag.txPower = inits.txPower(ii); % SINR comms model transmit power (W)
end
agentList{ii} = ag;
end
% ---- Build obstacles ---------------------------------------------------------
numObstacles = inits.numObstacles;
obstacleList = cell(numObstacles, 1);
if numObstacles > 0
for ii = 1:numObstacles
obs = rectangularPrism;
obs = obs.initialize([inits.obsMinCorners(ii, :); inits.obsMaxCorners(ii, :)], ...
REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii));
obstacleList{ii} = obs;
end
end
% ---- Optional backward-compat fields -----------------------------------------
if isfield(inits, 'useDoubleIntegrator')
useDoubleIntegrator = logical(inits.useDoubleIntegrator);
else
useDoubleIntegrator = false;
end
if isfield(inits, 'dampingCoeff')
dampingCoeff = inits.dampingCoeff;
else
dampingCoeff = 2.0;
end
if isfield(inits, 'useFixedTopology')
useFixedTopology = logical(inits.useFixedTopology);
else
useFixedTopology = false;
end
if isfield(inits, 'useSinrComms')
useSinrComms = logical(inits.useSinrComms);
else
useSinrComms = false;
end
if isfield(inits, 'sinrThreshold')
sinrThreshold = inits.sinrThreshold;
else
sinrThreshold = 0;
end
if isfield(inits, 'pathLossExponent')
pathLossExponent = inits.pathLossExponent;
else
pathLossExponent = 2.0;
end
if isfield(inits, 'ambientTemp')
ambientTemp = inits.ambientTemp;
else
ambientTemp = 290.0;
end
if isfield(inits, 'centerFreq')
centerFreq = inits.centerFreq;
else
centerFreq = 2.4e9;
end
if isfield(inits, 'bandwidth')
bandwidth = inits.bandwidth;
else
bandwidth = 20e6;
end
if isfield(inits, 'useRoutingTopology')
useRoutingTopology = logical(inits.useRoutingTopology);
else
useRoutingTopology = false;
end
% ---- Initialize simulation (plots and video disabled) ------------------------
obj = obj.initialize(dom, agentList, inits.barrierGain, inits.barrierExponent, ...
inits.minAlt, inits.timestep, inits.maxIter, obstacleList, ...
false, false, useDoubleIntegrator, dampingCoeff, useFixedTopology, false, ...
useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth, ...
useRoutingTopology);
end
-372
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@@ -1,372 +0,0 @@
function obj = lesserSinkNeighbor(obj)
% LESSERSINKNEIGHBOR Capacity-Aware Lesser Sink Neighbor algorithm (CALSN).
%
% Implements the algorithm specified in new/new_routing_algorithm.pdf as the
% selectable alternative to lesserNeighbor. UAVs 1 and N are base stations;
% every other UAV generates r = 1 unit of data per step, and all data must
% reach a base station. The algorithm outputs both a sparse maintained
% topology and a routing table.
%
% 1. Base-station potentials phi via distributed Bellman-Ford over the
% current communication neighborhoods (obj.adjacency), with link cost
% c_ij = 1/(C_ij + eps), where C_ij = bandwidth * log2(1 + SINR_ij) is
% the Shannon capacity of direction i -> j.
% 2. Lesser sink neighbors L_i replace LNA's "j < i" rule:
% L_i = { j in N_i : phi_j < phi_i, or phi_j == phi_i and j < i }.
% The equal-potential lexicographic tie-break is a documented deviation
% from the spec's strict inequality: at an exact potential watershed
% (e.g. a symmetric chain) the strict rule would split A_control into
% one tree per base station; the tie-break keeps the airborne graph
% connected, which the mission requires.
% 3. LNA-style sparsity: one parent per connected component of the
% L_i-induced subgraph (only links with positive capacity in at least
% one direction count as edges), chosen by
% p = argmin_{j in C} ( phi_j + 1/(C_ij + eps) ).
% A_control(i,p) = A_control(p,i) = 1 (diagonal = I).
% BASIN EXTENSION (documented deviation): with two potential minima
% (the two bases), one-parent-per-component alone yields a spanning
% forest with up to two disjoint base-rooted trees whenever a UAV's
% lesser sink neighbors collapse into a single component (dense usable
% graphs). To restore LNA's global-connectivity property, each UAV
% selects one representative per component AND per base-station BASIN
% (the base a neighbor's potential descent terminates at). Interior
% UAVs are unaffected (their whole neighborhood shares one basin);
% watershed UAVs whose neighborhoods span both basins gain a second
% parent, which is exactly the bridge between the two trees. A final
% stitch guard covers degenerate geometries: if A_control still has
% multiple components, the lowest-cost feasible inter-component link
% is added (maintained for connectivity only; carries no flow).
% 4. Routing, children first (decreasing phi; equal phi processed in
% decreasing index order so tie-break children precede their parents):
% aggregate demand D_i = r + inflows, split capacity-proportionally
% over parents; saturated links are capped at capacity and the residual
% redistributed over unsaturated parents; any demand beyond the total
% parent capacity is reported as unrouted and the UAV marked infeasible.
%
% Outputs (set on obj):
% constraintAdjacencyMatrix A_control: undirected maintained topology
% routingFlows F: flow on each directed link (units of r)
% routingFractions R = F/D: share of the sender's demand, 0..1
% routingAdjacencyMatrix F > 0 (directed, child -> parent)
% routingPotentials phi (base-station potential per UAV)
% routingUnrouted unrouted demand per UAV (zeros when feasible)
arguments (Input)
obj (1, 1) {mustBeA(obj, "miSim")};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "miSim")};
end
nAgents = size(obj.agents, 1);
r = 1.0; % data generated per non-base UAV per step (abstract unit)
EPS_CAP = 1e-12; % epsilon in c = 1/(C + eps); avoids division by zero
TOL = 1e-12; % residual-demand tolerance for the saturation loop
isBase = false(nAgents, 1);
isBase(1) = true;
isBase(nAgents) = true; % base stations are UAVs 1 and N
positions = zeros(nAgents, 3);
for kk = 1:nAgents
positions(kk, :) = obj.agents{kk}.pos;
end
% Directed Shannon link capacities over the current communication
% neighborhoods: C(i, j) = capacity of sending from i to j (receiver j)
C = zeros(nAgents);
for ii = 1:nAgents
for jj = 1:nAgents
if jj ~= ii && obj.adjacency(ii, jj)
C(ii, jj) = obj.bandwidth * log2(1 + obj.sinrLink(positions, jj, ii));
end
end
end
% ---- Base-station potentials (Bellman-Ford, at most N-1 sweeps) -----
phi = inf(nAgents, 1);
phi(isBase) = 0;
for sweep = 1:max(nAgents - 1, 1)
changed = false;
for ii = 1:nAgents
if isBase(ii)
continue;
end
newPhi = inf;
for jj = 1:nAgents
if jj == ii || ~obj.adjacency(ii, jj)
continue;
end
newPhi = min(newPhi, phi(jj) + 1 / (C(ii, jj) + EPS_CAP));
end
if newPhi ~= phi(ii)
phi(ii) = newPhi;
changed = true;
end
end
if ~changed
break;
end
end
% ---- Base-station basins (for the basin extension) -------------------
% Each finite-potential UAV descends its argmin neighbor chain; phi is
% strictly decreasing along it, so the chain terminates at a base. The
% basin label records which base that is.
descent = zeros(nAgents, 1);
for ii = 1:nAgents
if isBase(ii) || isinf(phi(ii))
continue;
end
bestMetric = inf;
for jj = 1:nAgents
if jj == ii || ~obj.adjacency(ii, jj)
continue;
end
metric = phi(jj) + 1 / (C(ii, jj) + EPS_CAP);
if metric < bestMetric
bestMetric = metric;
descent(ii) = jj;
end
end
end
basin = zeros(nAgents, 1);
basin(1) = 1;
basin(nAgents) = nAgents;
for ii = 1:nAgents
if isBase(ii) || isinf(phi(ii))
continue;
end
kk = ii;
while ~isBase(kk)
kk = descent(kk);
end
basin(ii) = kk;
end
% ---- Parent selection (one per lesser-sink component and basin) ------
Acontrol = logical(eye(nAgents));
isParent = false(nAgents); % isParent(i, p): p is a selected parent of i
for ii = 1:nAgents
if isBase(ii) || isinf(phi(ii))
% Base stations select no parents; an infinite potential means
% no current local route toward a base station
continue;
end
% Lesser sink neighbors (with the equal-potential tie-break)
lsnBuf = zeros(1, nAgents);
lsnCount = 0;
for jj = 1:nAgents
if jj == ii || ~obj.adjacency(ii, jj)
continue;
end
if phi(jj) < phi(ii) || (phi(jj) == phi(ii) && jj < ii)
lsnCount = lsnCount + 1;
lsnBuf(lsnCount) = jj;
end
end
if lsnCount == 0
continue;
end
lsn = lsnBuf(1:lsnCount);
% Subgraph induced by the lesser sink neighbors in the usable
% communication graph: only links with positive capacity in at
% least one direction count as edges (a zero-capacity link cannot
% carry data, so it must not merge two components)
subgraphAdjacency = false(lsnCount);
for aa = 1:lsnCount
for bb = (aa + 1):lsnCount
ja = lsn(aa);
jb = lsn(bb);
if obj.adjacency(ja, jb) && (C(ja, jb) > 0 || C(jb, ja) > 0)
subgraphAdjacency(aa, bb) = true;
subgraphAdjacency(bb, aa) = true;
end
end
end
% One parent per connected component and per base-station basin
% present in it (basin extension), selected by capacity and
% potential: p = argmin( phi_j + 1/(C_ij + eps) )
visited = false(1, lsnCount);
for aa = 1:lsnCount
if visited(aa)
continue;
end
component = bfs(subgraphAdjacency, aa);
visited(component) = true;
for bb = [1, nAgents] % the two possible basin labels
bestMetric = inf;
bestParent = 0;
for cc = 1:numel(component)
jj = lsn(component(cc));
if basin(jj) ~= bb
continue;
end
metric = phi(jj) + 1 / (C(ii, jj) + EPS_CAP);
if metric < bestMetric
bestMetric = metric;
bestParent = jj;
end
end
if bestParent > 0
isParent(ii, bestParent) = true;
Acontrol(ii, bestParent) = true;
Acontrol(bestParent, ii) = true;
end
end
end
end
% ---- Connectivity stitch guard ---------------------------------------
% The basin extension bridges the two base-rooted trees through
% watershed UAVs whenever each base borders a routing basin. Degenerate
% geometries (e.g. a base whose only feasible neighbor is the other
% base) can still leave A_control split; add the lowest-cost feasible
% link between components until one remains. Stitched links are
% maintained for connectivity only and carry no routed flow. If the
% feasibility graph itself is disconnected no stitch exists; validate()
% reports that case.
while true
comp = zeros(1, nAgents);
nComp = 0;
for ii = 1:nAgents
if comp(ii) == 0
nComp = nComp + 1;
comp(bfs(Acontrol, ii)) = nComp;
end
end
if nComp <= 1
break;
end
bestMetric = inf;
bestU = 0;
bestV = 0;
for uu = 1:nAgents
for vv = (uu + 1):nAgents
if comp(uu) ~= comp(vv) && obj.adjacency(uu, vv)
% Bidirectional link cost (finite even for infinite
% potentials, so isolated islands remain stitchable)
metric = 1 / (C(uu, vv) + EPS_CAP) + 1 / (C(vv, uu) + EPS_CAP);
if metric < bestMetric
bestMetric = metric;
bestU = uu;
bestV = vv;
end
end
end
end
if bestU == 0
break; % feasibility graph disconnected: nothing to stitch with
end
Acontrol(bestU, bestV) = true;
Acontrol(bestV, bestU) = true;
end
% ---- Routing (children first: decreasing potential order) -----------
% Equal potentials are processed in decreasing index order: with the
% lexicographic tie-break, flow within an equal-potential group goes
% from higher to lower index, so higher indices must aggregate first.
F = zeros(nAgents);
R = zeros(nAgents);
unrouted = zeros(nAgents, 1);
nonBase = find(~isBase);
[~, ord] = sortrows([phi(nonBase), nonBase], [-1, -2]);
order = nonBase(ord);
for oo = 1:numel(order)
ii = order(oo);
% Aggregated outgoing demand: own data plus everything received
D = r + sum(F(:, ii));
parents = find(isParent(ii, :));
if D == 0 || isempty(parents)
continue;
end
% Capacity-proportional split, saturating full links first and
% redistributing the remainder across parents with remaining
% capacity. Each pass either routes all residual demand or
% saturates at least one parent, so the loop terminates.
capP = C(ii, parents);
flows = zeros(1, numel(parents));
active = true(1, numel(parents));
residual = D;
while residual > TOL && any(active)
totalCap = sum(capP(active));
if totalCap <= 0
break;
end
alloc = zeros(1, numel(parents));
alloc(active) = residual .* capP(active) ./ totalCap;
flows = flows + alloc;
saturated = active & (flows > capP);
if any(saturated)
residual = sum(flows(saturated) - capP(saturated));
flows(saturated) = capP(saturated);
active(saturated) = false;
else
residual = 0;
end
end
if residual > TOL
% Demand exceeds the total parent capacity: route as much as
% possible and report the remainder as unrouted (infeasible)
unrouted(ii) = residual;
warning("miSim:routingInfeasible", ...
"UAV %d demand %.3g exceeds total parent capacity; %.3g units unrouted", ...
ii, D, residual);
end
F(ii, parents) = flows;
R(ii, parents) = flows ./ D;
end
% ---- Outputs ---------------------------------------------------------
obj.constraintAdjacencyMatrix = Acontrol;
obj.routingFlows = F;
obj.routingFractions = R;
obj.routingAdjacencyMatrix = F > 0;
obj.routingPotentials = phi;
obj.routingUnrouted = unrouted;
end
function cComp = bfs(subgraphAdjacency, startIdx)
% Breadth-first search returning the connected component of startIdx.
% Pre-allocated queue and component buffer with head/tail pointers to
% avoid element deletion and dynamic array growth (same pattern as the
% local bfs in lesserNeighbor.m).
n = size(subgraphAdjacency, 1);
visited = false(1, n);
queue = zeros(1, n);
cCompBuf = zeros(1, n);
qHead = 1;
qTail = 2;
queue(1) = startIdx;
cCompBuf(1) = startIdx;
cSize = 1;
visited(startIdx) = true;
while qHead < qTail
current = queue(qHead);
qHead = qHead + 1;
neighbors = find(subgraphAdjacency(current, :));
for kk = 1:numel(neighbors)
neighbor = neighbors(kk);
if ~visited(neighbor)
visited(neighbor) = true;
cCompBuf(cSize + 1) = neighbor;
cSize = cSize + 1;
queue(qTail) = neighbor;
qTail = qTail + 1;
end
end
end
cComp = sort(cCompBuf(1:cSize));
end
+4 -34
View File
@@ -7,6 +7,7 @@ classdef miSim
timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
maxIter = NaN; % maximum number of simulation iterations
domain;
objective;
obstacles; % geometries that define obstacles within the domain
agents; % agents that move within the domain
adjacency = false(0, 0); % Adjacency matrix representing communications network graph
@@ -17,39 +18,11 @@ classdef miSim
barrierGain = NaN; % CBF gain parameter
barrierExponent = NaN; % CBF exponent parameter
minAlt = 0; % minimum allowable altitude (m)
useDoubleIntegrator = false; % false = single-integrator, true = double-integrator dynamics
dampingCoeff = 2.0; % velocity-proportional damping for double-integrator mode
useFixedTopology = false; % false = lesser neighbor (dynamic), true = fixed initial topology
optimizeSensorPointing = false; % false = fixed sensor tilt/azimuth, true = optimize tilt/azimuth via gradient ascent
% Communications model selection and SINR-model parameters.
% useSinrComms = false -> fixed-radius comms (comRange / commsGeometry).
% useSinrComms = true -> SINR/path-loss comms (txPower + params below).
useSinrComms = false;
sinrThreshold = 0; % SINR threshold for connectivity & CBF maintenance (dB)
pathLossExponent = 2.0; % path-loss exponent n in S = P / (K * d^n)
ambientTemp = 290.0; % ambient temperature (K) for thermal noise N = k_B*T*B
centerFreq = 2.4e9; % carrier frequency (Hz); sets path-loss offset K = (4*pi*f_c/c)^2
bandwidth = 20e6; % channel bandwidth (Hz) for thermal noise N = k_B*T*B
% Topology-selection algorithm (requires useSinrComms; MATLAB sim only).
% false -> lesser-neighbor; true -> Capacity-Aware Lesser Sink Neighbor
% (CALSN, see new/new_routing_algorithm.pdf): base-station potentials
% replace the index-based "lesser" rule, and the maintained topology
% comes with a routing table (flows F, fractions R) that sends every
% UAV's data toward base stations 1 and N.
useRoutingTopology = false;
routingAdjacencyMatrix = false(0, 0); % directed flow links (i, j) = child i sends to parent j (F > 0)
routingFlows = zeros(0, 0); % F: flow on each directed link (units of r = 1 per UAV per step)
routingFractions = zeros(0, 0); % R = F/D: share of the sender's aggregated demand per link (0..1)
routingPotentials = zeros(0, 1); % phi: Bellman-Ford base-station potential per UAV
routingUnrouted = zeros(0, 1); % unrouted demand per UAV (zeros when routing is feasible)
artifactName = "";
f; % main plotting tiled layout figure
fPerf; % performance plot figure
% Indicies for various plot types in the main tiled layout figure
spatialPlotIndices = [6, 4, 3, 2];
numBarriers = 0; % Number of barrier functions needed
barriers = []; % log barrier function values at each timestep for analysis
constraintAdjacencyHist = []; % log constraint adjacency matrix at each timestep
end
properties (Access = private)
@@ -67,7 +40,6 @@ classdef miSim
performancePlot; % objects for sensor performance plot
posHist; % data for trail plot
velHist; % velocity history (double-integrator mode)
trailPlot; % objects for agent trail plot
% Indicies for various plot types in the main tiled layout figure
@@ -76,6 +48,7 @@ classdef miSim
partitionGraphIndex = 1;
% CBF plotting
h; % h function values
hf; % h function plotting figure
caPlot; % objects for collision avoidance h function plot
obsPlot; % objects for obstacle h function plot
@@ -88,18 +61,15 @@ classdef miSim
obj (1, 1) miSim
end
obj.domain = rectangularPrism;
obj.objective = sensingObjective;
obj.obstacles = {rectangularPrism};
obj.agents = {agent};
end
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology, optimizeSensorPointing, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth, useRoutingTopology);
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo);
[obj] = initializeFromCsv(obj, csvPath);
[obj] = initializeFromInits(obj, initsPath);
[obj] = plotFromSimHist(obj, initsPath, histPath);
[obj] = run(obj);
[obj] = lesserNeighbor(obj);
[obj] = lesserSinkNeighbor(obj);
[obj] = constrainMotion(obj);
[sinr, grad] = sinrLink(obj, positions, rxIdx, txIdx);
[obj] = partition(obj);
[obj] = updateAdjacency(obj);
[obj] = plot(obj);
-93
View File
@@ -1,93 +0,0 @@
function obj = plotFromSimHist(obj, initsPath, histPath)
% PLOTFROMSIMHIST Reconstruct all three miSim plots from saved matfiles.
%
% Loads the simInits matfile to rebuild domain/obstacle/objective/agent
% geometry, then loads the simHist matfile to restore the full time-history
% arrays. Produces the same three figures that a live run would generate:
% 1. Sensor performance vs. time (obj.fPerf)
% 2. Barrier function values vs. time (obj.hf)
% 3. 3-D spatial figure with domain, obstacles, objective, agent trails,
% and final-timestep communications topology (obj.f)
%
% Usage:
% sim = miSim;
% sim = sim.plotFromSimHist( ...
% 'sandbox/2025_01_01_12_00_00_miSimHist.mat', ...
% 'sandbox/2025_01_01_12_00_00_miSimInits.mat');
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
initsPath (1, 1) string;
histPath (1, 1) string;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
% ---- Reconstruct geometry from inits (plots disabled) --------------------
obj = obj.initializeFromInits(initsPath);
nAgents = size(obj.agents, 1);
% ---- Load history data ---------------------------------------------------
data = load(histPath);
out = data.out;
nHistTimesteps = size(out.barriers, 2);
nPosTimesteps = size(out.agent(1).pos, 1);
% ---- Populate barrier history --------------------------------------------
% out.barriers may be narrower than the pre-allocated obj.barriers if the
% run was shorter than maxIter; fill what we have and leave the rest NaN.
obj.barriers(:, 1:nHistTimesteps) = out.barriers;
% ---- Populate position history and advance agents to final positions -----
for ii = 1:nAgents
agentPos = out.agent(ii).pos; % (nPosTimesteps × 3)
nPts = size(agentPos, 1);
obj.posHist(ii, 1:nPts, :) = reshape(agentPos, [1, nPts, 3]);
obj.agents{ii}.pos = agentPos(end, :); % show final position in spatial plot
end
% ---- Set final constraint topology ---------------------------------------
obj.constraintAdjacencyMatrix = out.constraintAdjacency(:, :, end);
% ---- Recompute partitioning at final agent positions ---------------------
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
% ---- Enable plotting and produce spatial + barrier figures ---------------
obj.makePlots = true;
obj = obj.plot();
% ---- Performance figure (built directly — live machinery is incremental) -
nPerfTimesteps = numel(out.perf);
times = (0:nPerfTimesteps - 1) * obj.timestep;
normFactor = 1 / max(out.perf);
obj.fPerf = figure;
ax = axes(obj.fPerf);
hold(ax, "on");
title(ax, "Sensor Performance");
xlabel(ax, "Time (s)");
ylabel(ax, "Sensor Performance");
grid(ax, "on");
legendStrings = strings(nAgents + 1, 1);
legendStrings(1) = "Total";
plot(ax, times, out.perf * normFactor, "LineWidth", 1.5);
for ii = 1:nAgents
agentPerf = out.agent(ii).perf;
agentTimes = times(1:numel(agentPerf));
plot(ax, agentTimes, agentPerf * normFactor);
if isfield(out.agent(ii), 'label')
legendStrings(ii + 1) = string(out.agent(ii).label);
else
legendStrings(ii + 1) = sprintf("Agent %d", ii);
end
end
legend(ax, legendStrings, "Location", "northwest");
hold(ax, "off");
% Bring spatial figure to the front
figure(obj.f);
end
+11 -70
View File
@@ -6,82 +6,23 @@ function obj = plotGraph(obj)
obj (1, 1) {mustBeA(obj, "miSim")};
end
% The maintained links are always drawn as a dotted undirected graph.
% In routing (CALSN) mode the flow-carrying links are overlaid as SOLID
% DIRECTED edges (arrow = child -> parent, toward a base station) on
% the same node layout.
% Form graph from adjacency matrix
G = graph(obj.constraintAdjacencyMatrix, "omitselfloops");
% Resolve the target axes for the network graph tile
% Plot graph object
if isnan(obj.networkGraphIndex)
ax = obj.f.CurrentAxes;
hold(obj.f.CurrentAxes, "on");
o = plot(obj.f.CurrentAxes, G, "LineStyle", "--", "EdgeColor", "g", "NodeColor", "k", "LineWidth", 2);
hold(obj.f.CurrentAxes, "off");
else
ax = obj.f.Children(1).Children(obj.networkGraphIndex(1));
end
% Plot graph object(s)
hold(ax, "on");
o = plot(ax, G, "LineStyle", "--", "EdgeColor", "g", "NodeColor", "k", "LineWidth", 2);
if obj.useRoutingTopology
% Flow overlay: reuse the base layout's node coordinates and hide
% the overlay's own nodes/labels so only its edges show. Sizeable
% arrowheads so the flow direction reads at tile size.
D = digraph(obj.routingAdjacencyMatrix);
o = [o; plot(ax, D, "XData", o(1).XData, "YData", o(1).YData, ...
"LineStyle", "-", "EdgeColor", "g", "LineWidth", 2, ...
"ArrowSize", 12, "Marker", "none", "NodeLabel", {})];
end
hold(ax, "off");
nBase = size(o, 1);
if ~isnan(obj.networkGraphIndex) && size(obj.networkGraphIndex, 2) > 1
for ii = 2:size(obj.networkGraphIndex, 2)
o = [o; copyobj(o(1:nBase), obj.f.Children(1).Children(obj.networkGraphIndex(ii)))];
end
end
% In SINR comms mode, label each edge with the connection's SINR and report
% the connectivity threshold in the tile title. The fixed-radius model is
% left unchanged (no edge labels, title stays as set in firstPlotSetup).
if obj.useSinrComms
endNodes = G.Edges.EndNodes;
nAgents = size(obj.agents, 1);
positions = zeros(nAgents, 3);
for kk = 1:nAgents
positions(kk, :) = obj.agents{kk}.pos;
end
% Labels are bare numbers (no units) so they stay compact; GraphPlot
% renders them horizontally, left-to-right. Dotted (maintained) edges
% are labelled with the binding (worse) directional SINR — a link is
% feasible only if BOTH directions clear the threshold. Links that
% also carry flow leave the label to the solid directed edge, which
% shows the flow value (units of r) sent child -> parent.
edgeLabels = strings(size(endNodes, 1), 1);
for ee = 1:size(endNodes, 1)
lo = endNodes(ee, 1);
hi = endNodes(ee, 2);
if obj.useRoutingTopology && (obj.routingAdjacencyMatrix(lo, hi) || obj.routingAdjacencyMatrix(hi, lo))
edgeLabels(ee) = ""; % solid overlay carries this link's label
else
sinrLoRx = obj.sinrLink(positions, lo, hi); % receiver lo (lower index)
sinrHiRx = obj.sinrLink(positions, hi, lo); % receiver hi (higher index)
edgeLabels(ee) = sprintf("%.1f", 10 * log10(min(sinrLoRx, sinrHiRx)));
hold(obj.f.Children(1).Children(obj.networkGraphIndex(1)), "on");
o = plot(obj.f.Children(1).Children(obj.networkGraphIndex(1)), G, "LineStyle", "--", "EdgeColor", "g", "NodeColor", "k", "LineWidth", 2);
hold(obj.f.Children(1).Children(obj.networkGraphIndex(1)), "off");
if size(obj.networkGraphIndex, 2) > 1
for ii = 2:size(ind, 2)
o = [o; copyobj(o(1), obj.f.Children(1).Children(obj.networkGraphIndex(ii)))];
end
end
o(1).EdgeLabel = edgeLabels;
if obj.useRoutingTopology
endNodesD = D.Edges.EndNodes; % each row [child parent]
flowLabels = strings(size(endNodesD, 1), 1);
for ee = 1:size(endNodesD, 1)
flowLabels(ee) = sprintf("%.2f", obj.routingFlows(endNodesD(ee, 1), endNodesD(ee, 2)));
end
o(2).EdgeLabel = flowLabels;
end
% Threshold goes in the existing single-line title (not a subtitle) so
% the small tile is not compressed further, and the hover toolbar is
% disabled so the R2026 "..." menu stops covering the readout.
title(ax, sprintf("Network Graph (\\geq %.1f dB)", obj.sinrThreshold));
ax.Toolbar.Visible = "off";
end
obj.graphPlot = o;
end
+4 -13
View File
@@ -6,10 +6,6 @@ function obj = plotH(obj)
obj (1, 1) {mustBeA(obj, "miSim")};
end
nCA = size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2;
nObs = size(obj.agents, 1) * size(obj.obstacles, 1);
nDom = size(obj.agents, 1) * 6;
obj.hf = figure;
tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
@@ -19,7 +15,7 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Collision Avoidance");
hold(obj.hf.Children(1).Children(1), "on");
obj.caPlot = plot(obj.barriers(1:nCA, :)');
obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)');
legendStrings = [];
for ii = 2:size(obj.agents, 1)
for jj = 1:(ii - 1)
@@ -35,7 +31,7 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Obstacles");
hold(obj.hf.Children(1).Children(1), "on");
obj.obsPlot = plot(obj.barriers((nCA + 1):(nCA + nObs), :)');
obj.obsPlot = plot(obj.h((1 + (size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)):(((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1)), :)');
legendStrings = [];
for ii = 1:size(obj.obstacles, 1)
for jj = 1:size(obj.agents, 1)
@@ -51,13 +47,8 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Domain");
hold(obj.hf.Children(1).Children(1), "on");
obj.domPlot = plot(obj.barriers((nCA + nObs + 1):(nCA + nObs + nDom), :)');
domLabels = ["X Min", "X Max", "Y Min", "Y Max", "Z Min", "Z Max"];
legendStrings = strings(nDom, 1);
for ii = 1:size(obj.agents, 1)
legendStrings((ii - 1) * 6 + (1:6)) = sprintf("A%d ", ii) + domLabels;
end
legend(obj.hf.Children(1).Children(1), legendStrings, "Location", "bestoutside");
obj.domPlot = plot(obj.h((1 + (((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1))):size(obj.h, 1), 1:end)');
legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], "Location", "bestoutside");
hold(obj.hf.Children(1).Children(2), "off");
nexttile(obj.hf.Children(1));
+5 -36
View File
@@ -10,13 +10,7 @@ function [obj] = run(obj)
% Start video writer
if obj.makeVideo
v = obj.setupVideoWriter();
drawnow;
v.open();
% Capture reference frame size; used to resize frames that deviate
% due to figure reflow during plot updates (e.g. in headless mode).
I_ref = getframe(obj.f);
v.writeVideo(I_ref);
videoFrameSize = [size(I_ref.cdata, 2), size(I_ref.cdata, 1)];
end
end
@@ -31,36 +25,17 @@ function [obj] = run(obj)
obj.validate();
end
% Clear RF sensor caches
if isa(obj.agents{1}.sensorModel, "rfSensor")
for ss = 1:size(obj.agents, 1)
obj.agents{ss}.sensorModel = obj.agents{ss}.sensorModel.clearRssCache;
end
end
% Update partitioning before moving (this one is strictly for
% plotting purposes, the real partitioning is done by the agents)
[obj.partitioning, obj.agents] = obj.agents{1}.partition(obj.agents, obj.domain.objective);
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
% Determine desired communications links: the Capacity-Aware Lesser
% Sink Neighbor algorithm replaces lesser-neighbor when selected
if ~obj.useFixedTopology
if coder.target('MATLAB') && obj.useRoutingTopology
obj = obj.lesserSinkNeighbor();
else
obj = obj.lesserNeighbor();
end
end
% Log constraint adjacency for this timestep
if coder.target('MATLAB')
obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
end
% Determine desired communications links
obj = obj.lesserNeighbor();
% Moving
% Iterate over agents to simulate their unconstrained motion
for jj = 1:size(obj.agents, 1)
obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep, obj.optimizeSensorPointing, obj.agents([1:(jj - 1), (jj + 1):size(obj.agents, 1)]));
obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents);
end
% Adjust motion determined by unconstrained gradient ascent using
@@ -68,9 +43,8 @@ function [obj] = run(obj)
obj = constrainMotion(obj);
if coder.target('MATLAB')
% Update agent position and velocity history arrays
% Update agent position history array
obj.posHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
obj.velHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.vel, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
% Update total performance
obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(obj.timestepIndex+1), obj.agents))];
@@ -84,20 +58,15 @@ function [obj] = run(obj)
% Write frame in to video
if obj.makeVideo
I = getframe(obj.f);
if size(I.cdata, 2) ~= videoFrameSize(1) || size(I.cdata, 1) ~= videoFrameSize(2)
I.cdata = imresize(I.cdata, [videoFrameSize(2), videoFrameSize(1)]);
end
v.writeVideo(I);
end
end
end
% Close video
if coder.target('MATLAB')
if obj.makeVideo
% Close video file
v.close();
end
end
end
-101
View File
@@ -1,101 +0,0 @@
function [sinr, grad] = sinrLink(obj, positions, rxIdx, txIdx)
% SINRLINK Linear SINR of the link txIdx -> rxIdx and its position gradient.
%
% Computes the signal-to-interference-plus-noise ratio seen at receiver rxIdx
% for the signal transmitted by txIdx, treating every other agent as an
% interferer at that receiver. Isotropic transmit/receive (no antenna gains).
%
% Returns the linear SINR and (optionally) its gradient with respect to every
% agent position, grad(a, :) = d(SINR)/d(p_a). The value is used by
% updateAdjacency (connectivity) and both the value and gradient by
% constrainMotion (the SINR CBF barrier).
%
% Model (linear power domain), receiver r = rxIdx, transmitter t = txIdx:
% S = P_t / (K * d_tr^n) % received signal at r from t (W)
% I = sum_{k != t,r} P_k / (K * d_kr^n) % interference at r from others (W)
% N = k_B * T * B % thermal noise (W)
% SINR = S / (N + I)
% with K = (4*pi*f_c/c)^2 and physical constants baked in below. The only
% tunables are per-agent txPower (P), pathLossExponent (n), ambientTemp (T),
% all read from obj; the SINR threshold is applied by the callers.
arguments (Input)
obj (1, 1) {mustBeA(obj, "miSim")};
positions (:, 3) double;
rxIdx (1, 1) double;
txIdx (1, 1) double;
end
arguments (Output)
sinr (1, 1) double;
grad (:, 3) double;
end
% Universal physical constants
k_B = 1.380649e-23; % Boltzmann constant (J/K)
c = 3e8; % speed of light (m/s)
% System parameters
f_c = obj.centerFreq; % carrier frequency (Hz)
B = obj.bandwidth; % channel bandwidth (Hz)
K = (4 * pi * f_c / c)^2; % free-space path-loss reference constant
n = obj.pathLossExponent;
T = obj.ambientTemp;
d0 = 1.0; % near-field distance floor (m)
nAgents = size(positions, 1);
grad = zeros(nAgents, 3);
r = rxIdx;
t = txIdx;
pr = positions(r, :);
% Thermal noise (always > 0, so the denominator never vanishes)
N = k_B * T * B;
% Signal term S (source = transmitter t)
P_t = obj.agents{t}.txPower;
dvec_t = positions(t, :) - pr;
d_t = max(norm(dvec_t), d0);
S = P_t / (K * d_t^n);
% Interference I = sum of received powers from every other agent at r
I = 0.0;
for k = 1:nAgents
if k == r || k == t
continue;
end
d_k = max(norm(positions(k, :) - pr), d0);
I = I + obj.agents{k}.txPower / (K * d_k^n);
end
D = N + I; % denominator: noise + interference
sinr = S / D;
% ---- Gradient (skip unless requested) -------------------------------
% For a received term P_x/(K*d_xr^n):
% d(term)/dp_x = -n*term/d_xr^2 * (p_x - p_r), d(term)/dp_r = -d(term)/dp_x
if nargout > 1
% Transmitter affects S only: dSINR/dp_t = (dS/dp_t)/D
dS_dpt = (-n * S / (d_t^2)) * dvec_t;
grad(t, :) = dS_dpt / D;
% Interferers affect I only; accumulate the receiver's I-contribution
dI_dpr = zeros(1, 3);
for k = 1:nAgents
if k == r || k == t
continue;
end
dvec_k = positions(k, :) - pr;
d_k = max(norm(dvec_k), d0);
term_k = obj.agents{k}.txPower / (K * d_k^n);
dterm_dpk = (-n * term_k / (d_k^2)) * dvec_k;
grad(k, :) = (-S / (D^2)) * dterm_dpk; % dSINR/dp_k
dI_dpr = dI_dpr - dterm_dpk; % d(term_k)/dp_r = -d(term_k)/dp_k
end
% Receiver affects both S and I
dS_dpr = -dS_dpt;
grad(r, :) = dS_dpr / D - (S / (D^2)) * dI_dpr;
end
end
+5 -32
View File
@@ -6,52 +6,25 @@ function obj = teardown(obj)
obj (1, 1) {mustBeA(obj, "miSim")};
end
% % Close plots
% close(obj.hf);
% close(obj.fPerf);
% close(obj.f);
% Log results into matfile
histPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", strcat(obj.artifactName, "_miSimHist.mat"));
out = struct("agent", repmat(struct("pos", [], "vel", [], "perf", [], "sensor", struct("alphaDist", [], "betaDist", [], "alphaTilt", [], "betaTilt", []), "collisionRadius", [], "commsRadius", []), size(obj.agents)), "perf", [], "barriers", [], "useDoubleIntegrator", [], "dampingCoeff", [], "useFixedTopology", []);
out.perf = obj.performance(1:(end - 1));
out.barriers = [zeros(size(obj.barriers(1:end, 1), 1), 1), obj.barriers(1:end, 1:(end - 1))];
out.dampingCoeff = obj.dampingCoeff;
out.useDoubleIntegrator = obj.useDoubleIntegrator;
out.useFixedTopology = obj.useFixedTopology;
out.constraintAdjacency = obj.constraintAdjacencyHist(:, :, 1:(end - 1));
for ii = 1:size(obj.agents, 1)
out.agent(ii).pos = squeeze(obj.posHist(ii, 1:(end - 1), 1:3));
out.agent(ii).vel = squeeze(obj.velHist(ii, 1:(end - 1), 1:3));
out.agent(ii).perf = obj.agents{ii}.performance(1:(end - 2));
out.agent(ii).sensor.alphaDist = obj.agents{ii}.sensorModel.alphaDist;
out.agent(ii).sensor.betaDist = obj.agents{ii}.sensorModel.betaDist;
out.agent(ii).sensor.alphaTilt = obj.agents{ii}.sensorModel.alphaTilt;
out.agent(ii).sensor.betaTilt = obj.agents{ii}.sensorModel.betaTilt;
out.agent(ii).collisionRadius = obj.agents{ii}.collisionGeometry.radius;
out.agent(ii).commsRadius = obj.agents{ii}.commsGeometry.radius;
end
save(histPath, "out");
% Close plots
close(obj.hf);
close(obj.fPerf);
close(obj.f);
% reset parameters
obj.timestep = NaN;
obj.timestepIndex = NaN;
obj.maxIter = NaN;
obj.domain = rectangularPrism;
obj.objective = sensingObjective;
obj.obstacles = cell(0, 1);
obj.agents = cell(0, 1);
obj.adjacency = NaN;
obj.constraintAdjacencyMatrix = NaN;
obj.constraintAdjacencyHist = [];
obj.partitioning = NaN;
obj.performance = 0;
obj.barrierGain = NaN;
obj.barrierExponent = NaN;
obj.useDoubleIntegrator = false;
obj.dampingCoeff = 2.0;
obj.useFixedTopology = false;
obj.artifactName = "";
end
+9 -34
View File
@@ -6,41 +6,16 @@ function obj = updateAdjacency(obj)
obj (1, 1) {mustBeA(obj, "miSim")};
end
nAgents = size(obj.agents, 1);
% Initialize assuming only self-connections
A = true(size(obj.agents, 1));
% Initialize assuming all agents are connected
A = true(nAgents);
if ~obj.useSinrComms
% Fixed-radius model: pair connected iff separation is within the
% smaller of the two comms radii.
for ii = 2:nAgents
for jj = 1:(ii - 1)
if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) > min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])
A(ii, jj) = false; % comm range violation
continue;
end
end
end
else
% SINR model: a link between a pair is feasible only if BOTH directional
% SINRs clear the threshold, i.e. each agent receives the other's signal
% above gammaLin (with interference from all other agents at the
% receiver). Every ordered pair (permutation) is evaluated; a single
% failing direction eliminates the undirected link.
gammaLin = 10^(obj.sinrThreshold / 10); % dB threshold -> linear
positions = zeros(nAgents, 3);
for kk = 1:nAgents
positions(kk, :) = obj.agents{kk}.pos;
end
for ii = 2:nAgents
for jj = 1:(ii - 1)
sinrLoRx = obj.sinrLink(positions, jj, ii); % receiver jj (lower), transmitter ii
sinrHiRx = obj.sinrLink(positions, ii, jj); % receiver ii (higher), transmitter jj
if sinrLoRx < gammaLin || sinrHiRx < gammaLin
A(ii, jj) = false; % at least one direction below threshold
continue;
end
% Check lower triangle off-diagonal connections
for ii = 2:size(A, 1)
for jj = 1:(ii - 1)
% Check that agents are not out of range
if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) > min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])
A(ii, jj) = false; % comm range violation
continue;
end
end
end
+5 -7
View File
@@ -61,15 +61,13 @@ function [obj] = updatePlots(obj)
end
% Update h function plots
nCA = size(obj.caPlot, 1);
nObs = size(obj.obsPlot, 1);
for ii = 1:nCA
obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
for ii = 1:size(obj.caPlot, 1)
obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
end
for ii = 1:nObs
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, obj.timestepIndex);
for ii = 1:size(obj.obsPlot, 1)
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex);
end
for ii = 1:size(obj.domPlot, 1)
obj.domPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + nObs + ii, obj.timestepIndex);
obj.domPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1) + size(obj.obsPlot, 1), obj.timestepIndex);
end
end
+5 -19
View File
@@ -5,28 +5,13 @@ function validate(obj)
arguments (Output)
end
%% Mode Validators
if obj.useRoutingTopology && ~obj.useSinrComms
error("Routing topology requires SINR comms mode (useSinrComms)");
end
if obj.useRoutingTopology && obj.useFixedTopology
error("useRoutingTopology and useFixedTopology are mutually exclusive topology selectors");
end
%% Communications Network Validators
if max(conncomp(graph(obj.adjacency))) ~= 1
error("Network is not connected");
end
% In routing (CALSN) mode the MAINTAINED topology itself must form a
% single connected component (basin extension + stitch guard invariant)
if obj.useRoutingTopology && max(conncomp(graph(obj.constraintAdjacencyMatrix))) ~= 1
error("Maintained routing topology (A_control) is not connected");
warning("Network is not connected");
end
if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all")
error("Eliminated network connections that were necessary");
warning("Eliminated network connections that were necessary");
end
%% Obstacle Validators
@@ -35,9 +20,10 @@ function validate(obj)
for kk = 1:size(obj.agents, 1)
P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner);
d = obj.agents{kk}.pos - P;
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 - 1e-3
error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, - dot(d, d) + obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2
warning("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
end
end
end
end
+10 -56
View File
@@ -5,72 +5,26 @@ function writeInits(obj)
arguments (Output)
end
% User-supplied obstacles only: initialize() appends a floor obstacle at
% the end when minAlt > 0, so exclude it here to avoid double-counting on
% reconstruction (initializeFromInits re-adds the floor via minAlt).
numInputObs = size(obj.obstacles, 1) - (obj.minAlt > 0);
userObstacles = obj.obstacles(1:numInputObs);
% Collect agent parameters
collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
if isprop(obj.agents{1}.sensorModel, "alphaDist")
% sigmoidSensor parameters
alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
% others to zero
lossExponent = zeros(size(obj.agents));
P_TX = zeros(size(obj.agents));
BW = zeros(size(obj.agents));
f_c = zeros(size(obj.agents));
G_RX_dBi = zeros(size(obj.agents));
beamwidthExponent = zeros(size(obj.agents));
elseif isprop(obj.agents{1}.sensorModel, "P_TX")
% rfSensor parameters
lossExponent = cellfun(@(x) x.sensorModel.lossExponent, obj.agents);
P_TX = cellfun(@(x) x.sensorModel.P_TX, obj.agents);
BW = cellfun(@(x) x.sensorModel.BW, obj.agents);
f_c = cellfun(@(x) x.sensorModel.f_c, obj.agents);
G_RX_dBi = cellfun(@(x) x.sensorModel.G_RX_dBi, obj.agents);
beamwidthExponent = cellfun(@(x) x.sensorModel.beamwidthExponent, obj.agents);
% others to zero
alphaDist = zeros(size(obj.agents));
betaDist = zeros(size(obj.agents));
alphaTilt = zeros(size(obj.agents));
betaTilt = zeros(size(obj.agents));
end
% joint parameters
tilt = cellfun(@(x) x.sensorModel.tilt, obj.agents);
azimuth = cellfun(@(x) x.sensorModel.azimuth, obj.agents);
alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
txPower = cellfun(@(x) x.txPower, obj.agents);
initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, userObstacles, 'UniformOutput', false));
obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, userObstacles, 'UniformOutput', false));
% Combine with simulation parameters
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter + 1, "minAlt", obj.minAlt, ...
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ...
"discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
"sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", numInputObs, ...
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
"useSinrComms", obj.useSinrComms, "sinrThreshold", obj.sinrThreshold, "pathLossExponent", obj.pathLossExponent, "ambientTemp", obj.ambientTemp, ...
"centerFreq", obj.centerFreq, "bandwidth", obj.bandwidth, "txPower", txPower, ... % SINR comms model parameters
"useRoutingTopology", obj.useRoutingTopology, ... % topology-selection algorithm (CALSN when true)
"tilt", tilt, "azimuth", azimuth, ... % joint sensor parameters
"alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ... % sigmoid sensor parameters
"lossExponent", lossExponent, "P_TX", P_TX, "BW", BW, "f_c", f_c, "G_RX_dBi", G_RX_dBi, "beamwidthExponent", beamwidthExponent, ... % RF sensor parameters
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, "alphaDist", alphaDist, ...
"betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
"pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
"domainMin", obj.domain.minCorner, "domainMax", obj.domain.maxCorner, ...
"obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
"objectiveIntegral", sum(obj.domain.objective.values(:)));
"pos", pos);
% Save all parameters to output file
initsFile = strcat(obj.artifactName, "_miSimInits");
-23
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@@ -1,23 +0,0 @@
function value = RSS(obj, d, dx, dy, dz)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
d (:, 1) double;
dx (:, 1) double;
dy (:, 1) double;
dz (:, 1) double;
end
arguments (Output)
value (:, 1) double
end
% Boresight unit vector: [st*sa, st*ca, -ct]
% Target direction unit vector: [dx, dy, dz] / d
% cos_theta = dot product of the two, computed without per-point trig.
st = sind(obj.tilt);
ct = cosd(obj.tilt);
sa = sind(obj.azimuth);
ca = cosd(obj.azimuth);
cos_theta = (st .* (dx .* sa + dy .* ca) - ct .* dz) ./ max(d, eps);
cos_theta = max(-1, min(1, cos_theta));
theta = acosd(cos_theta);
value = obj.P_TX_dBm + obj.transmitterGain(theta) + obj.G_RX_dBi - obj.pathLoss(d);
end
-11
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@@ -1,11 +0,0 @@
function obj = clearRssCache(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "rfSensor")};
end
obj.rssCache = double.empty(0, 1);
end
-6
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@@ -1,6 +0,0 @@
function [d, dx, dy, dz] = computePointToPoints(~, agentPos, targetPos)
dx = targetPos(:,1) - agentPos(1);
dy = targetPos(:,2) - agentPos(2);
dz = targetPos(:,3) - agentPos(3);
d = sqrt(dx.^2 + dy.^2 + dz.^2);
end
-19
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@@ -1,19 +0,0 @@
function value = halfAngle(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
end
arguments (Output)
value (1, 1) double;
end
dtheta = (0:0.1:179.9)';
gain = obj.transmitterGain(dtheta);
target = gain(1) - 3;
idx = find(gain <= target, 1);
if isempty(idx) || idx == 1
value = dtheta(end);
return;
end
% Linear interpolation between bracketing samples
value = dtheta(idx-1) + (target - gain(idx-1)) * ...
(dtheta(idx) - dtheta(idx-1)) / (gain(idx) - gain(idx-1));
end
-35
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@@ -1,35 +0,0 @@
function obj = initialize(obj, txPower, temperature, bandwidth, centerFreq, rxGain_dBi, beamwidthExponent, tilt, azimuth, lossExponent)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")}
txPower (1, 1) double;
temperature (1, 1) double;
bandwidth (1, 1) double;
centerFreq (1, 1) double;
rxGain_dBi (1, 1) double;
beamwidthExponent (1, 1) double;
tilt (1, 1) double = 0;
azimuth (1, 1) double = 0;
lossExponent (1, 1) double = NaN;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "rfSensor")}
end
%% Provided values
obj.P_TX = txPower; % Transmit power (W)
obj.T_0 = temperature; % Temperature (K)
obj.BW = bandwidth; % Bandwidth (Hz)
obj.f_c = centerFreq; % Center frequency (Hz)
obj.G_RX_dBi = rxGain_dBi; % Receiving Antenna Gain (dBi)
obj.beamwidthExponent = beamwidthExponent; % Defines how focused the antenna beam is
obj.lossExponent = lossExponent;
% Define initial antenna pointing
obj.tilt = tilt;
obj.azimuth = azimuth;
%% Computed values
obj.P_TX_dBm = 10*log10(obj.P_TX/1e-3); % Transmit power in dBm
obj.N = obj.k_B * obj.T_0 * obj.BW; % Thermal noise
obj.constantGainTerm_dB = 10 .* log10(2 * (obj.beamwidthExponent + 1)); % used in RSS calculation, only need to compute once
end
-13
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@@ -1,13 +0,0 @@
function L_FSPL_dB = pathLoss(obj, d)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
d (:, 1) double; % distance from TX to RX
end
arguments (Output)
L_FSPL_dB (:, 1) double
end
% Free Space Path Loss (dB); d clamped away from zero (log undefined at d=0)
L_FSPL_dB = obj.lossExponent * 10 * log10(max(d, eps)) + 20 * log10((4 * pi * obj.f_c) / obj.c);
end
-125
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@@ -1,125 +0,0 @@
function f = plot(obj, altitude, otherSensorsPos, otherSensors)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
altitude (1, 1) double;
otherSensorsPos (:, 3) double = NaN(0, 3);
otherSensors (:, 1) cell = cell(0, 1);
end
arguments (Output)
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
end
% Clear local caches so this visualization always uses its own grid
obj.rssCache = [];
for ii = 1:numel(otherSensors)
otherSensors{ii}.rssCache = [];
end
% bias other sensors altitudes appropriately
otherSensorsPos = otherSensorsPos + [0, 0, altitude];
% Create grid on which to evalute SINR, SNR
agentPos = [0, 0, altitude];
d = 10;
if ~isempty(otherSensorsPos)
d = max(otherSensorsPos(:, 3) * 0.55);
d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
end
c = 0.1;
d = ceil(d / c) * c;
distances = -d:c:d;
[targetPosX, targetPosY] = meshgrid(distances, distances);
% Compute SINR, SNR
[SINR, ~] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
SINR = reshape(SINR, size(targetPosX));
% normalize in linear scale
% SINR = 10.^(SINR/10); SINR = SINR ./ max(SINR(:)); SINR = 10 * log10(SINR);
% Collect sensor positions and boresight parameters for overlay
sensorTilts = [obj.tilt; cellfun(@(s) s.tilt, otherSensors)];
sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
tailScale = 0.5 * d;
f = figure;
surf(targetPosX, targetPosY, zeros(size(targetPosX)), SINR, "EdgeColor", "none");
axis(f.Children(1), "image");
colormap(f.Children(1), "hot");
title("Ground User SINR and -3 dB antenna gain regions");
subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
c = colorbar;
ylabel(c, "SINR (dB)");
xlabel("X (m)");
ylabel("Y (m)");
hold(f.Children(2), "on");
scatter3(0, 0, altitude, 100, 'ko', "LineWidth", 2);
scatter3(otherSensorsPos(:, 1), otherSensorsPos(:, 2), otherSensorsPos(:, 3), 100, "bx", "LineWidth", 2);
qSelf = quiver3(0, 0, altitude, ...
tailScale * sind(obj.tilt) * sind(obj.azimuth), ...
tailScale * sind(obj.tilt) * cosd(obj.azimuth), ...
-tailScale * cosd(obj.tilt), ...
0, 'k', 'LineWidth', 1.5);
qSelf.MaxHeadSize = 0.75;
if ~isempty(otherSensors)
qOthers = quiver3(otherSensorsPos(:,1), otherSensorsPos(:,2), otherSensorsPos(:,3), ...
tailScale .* sind(sensorTilts(2:end)) .* sind(sensorAzimuths(2:end)), ...
tailScale .* sind(sensorTilts(2:end)) .* cosd(sensorAzimuths(2:end)), ...
-tailScale .* cosd(sensorTilts(2:end)), ...
0, 'b', 'LineWidth', 1.5);
qOthers.MaxHeadSize = 0.75;
end
% Draw half-angle cones co-boresighted with each quiver arrow
N = 48;
phi = linspace(0, 2*pi, N);
[PHI, S] = meshgrid(phi, [0; 1]); % row 1 = apex (s=0), row 2 = base (s=1)
allSensors = [{obj}; otherSensors];
allPos = [[0, 0, altitude]; otherSensorsPos];
for ii = 1:numel(allSensors)
ha = allSensors{ii}.halfAngle();
tlt = sensorTilts(ii);
az = sensorAzimuths(ii);
pos = allPos(ii, :);
% Cone length: enough that the axis tip is guaranteed below z=0
coneLength = 1.1 * pos(3) / max(cosd(tlt), 0.1);
% Nadir cone mesh: apex at origin, base at z = -coneLength
cX = S .* coneLength .* tand(ha) .* cos(PHI);
cY = S .* coneLength .* tand(ha) .* sin(PHI);
cZ = -S .* coneLength;
% Rotate nadir → boresight (same convention as quiver arrows)
Ry = [cosd(tlt), 0, -sind(tlt); 0, 1, 0; sind(tlt), 0, cosd(tlt)];
Rz = [sind(az), -cosd(az), 0; cosd(az), sind(az), 0; 0, 0, 1];
R = Rz * Ry;
pts = R * [cX(:)'; cY(:)'; cZ(:)'];
cX = reshape(pts(1,:), size(cX)) + pos(1);
cY = reshape(pts(2,:), size(cY)) + pos(2);
cZ = reshape(pts(3,:), size(cZ)) + pos(3);
if ii == 1
fc = [0, 0, 0];
else
fc = [0, 0, 1];
end
surf(cX, cY, cZ, "FaceColor", fc, "FaceAlpha", 0.15, "EdgeColor", "none");
% Conic section: intersect each cone generator with z=0
b_vec = R * [0; 0; -1];
u_vec = R * [1; 0; 0];
v_vec = R * [0; 1; 0];
phi_sec = linspace(0, 2*pi, 720)';
dirs = cosd(ha) .* b_vec' + sind(ha) .* (cos(phi_sec) .* u_vec' + sin(phi_sec) .* v_vec');
t_sec = -pos(3) ./ dirs(:, 3);
t_sec(t_sec <= 0) = NaN;
sx = pos(1) + t_sec .* dirs(:, 1);
sy = pos(2) + t_sec .* dirs(:, 2);
plot3(sx, sy, zeros(size(sx)), "Color", fc, "LineWidth", 2);
end
clim(f.Children(2), [min(SINR(:)), max(SINR(:))]);
xlim(f.Children(2), [-d, d]);
ylim(f.Children(2), [-d, d]);
hold(f.Children(2), "off");
zlim([0, Inf]);
end
-55
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@@ -1,55 +0,0 @@
function f = plotParameters(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
end
arguments (Output)
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
end
% Agent altitude layers and angle sample points
alt_values = 10.^[1, 2, 3, 4];
t_values = 0:2.5:87.5; % 0=nadir (center), <90=near horizon (edge)
a_values = 0:2.5:360;
[T, A] = meshgrid(t_values, a_values); % Naz x Nel
Ar = deg2rad(A);
f = figure;
hold("on");
for ii = 1:numel(alt_values)
alt = alt_values(ii);
% For agent at altitude alt, ground target at tilt T has slant distance:
D = alt ./ cosd(T);
% Convert LOS (D, T, A) to displacement vectors for RSS
dx = D .* sind(T) .* sind(A);
dy = D .* sind(T) .* cosd(A);
dz = -D .* cosd(T); % negative: ground targets are below agent
rss = obj.RSS(D(:), dx(:), dy(:), dz(:));
Fslice = reshape(rss, size(D));
% Disc geometry: t=0 (nadir) -> center, t~90 (horizon) -> edge
r = log10(alt) .* T ./ 90;
X = r .* cos(Ar);
Y = r .* sin(Ar);
Z = log10(alt) * ones(size(X));
hs = surf(X, Y, Z, Fslice);
hs.EdgeColor = 'none';
hs.FaceColor = 'interp';
hs.FaceAlpha = 0.25;
end
colormap(turbo);
c = colorbar; c.Label.String = "Received Signal Strength (dB)";
daspect([1 1 0.2]);
xlabel('X (log_{10} units)'); ylabel('Y (log_{10} units)'); zlabel('log_{10} Altitude (m)');
set(gca, 'ZDir', 'reverse');
view(3);
axis("vis3d");
grid("on");
scatter3(0, 0, 0, 'rx');
hold("off");
end
-89
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@@ -1,89 +0,0 @@
function f = plotPerformance(obj, altitude, otherSensorsPos, otherSensors)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
altitude (1, 1) double;
otherSensorsPos (:, 3) double = NaN(0, 3);
otherSensors (:, 1) cell = cell(0, 1);
end
arguments (Output)
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
end
% Clear local caches so this visualization always uses its own grid
obj.rssCache = [];
for ii = 1:numel(otherSensors)
otherSensors{ii}.rssCache = [];
end
% bias other sensors altitudes appropriately
otherSensorsPos = otherSensorsPos + [0, 0, altitude];
% Create grid on which to evalute SINR, SNR
agentPos = [0, 0, altitude];
d = 10;
if ~isempty(otherSensorsPos)
d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
end
c = 0.1;
d = ceil(d / c) * c;
distances = -d:c:d;
[targetPosX, targetPosY] = meshgrid(distances, distances);
% Compute SINR, SNR
[SINR, SNR] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
SINR = reshape(SINR, size(targetPosX));
SNR = reshape(SNR, size(targetPosX));
% Collect sensor positions and boresight parameters for overlay
sensorXY = [0, 0; otherSensorsPos(:, 1:2)];
sensorTilts = [obj.tilt; cellfun(@(s) s.tilt, otherSensors)];
sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
tailScale = 0.5 * d;
f = figure;
tiledlayout(1, 2, TileSpacing="compact", Padding="compact");
nexttile;
imagesc(distances, distances, SNR);
axis("image"); set(gca, 'YDir', 'normal');
cb = colorbar; cb.Label.String = "SNR (dB)";
xlabel("X (m)"); ylabel("Y (m)");
title("Linearly Normalized SNR (dB)");
subtitle("No interfering sources");
addSensorOverlay(gca, sensorXY(1, 1:2), sensorTilts(1, 1), sensorAzimuths(1, 1), tailScale);
nexttile;
imagesc(distances, distances, SINR);
axis("image"); set(gca, 'YDir', 'normal');
cb = colorbar; cb.Label.String = "SNR (dB)";
xlabel("X (m)"); ylabel("Y (m)");
title("Linearly Normalized SINR (dB)");
subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
addSensorOverlay(gca, sensorXY, sensorTilts, sensorAzimuths, tailScale);
end
function addSensorOverlay(ax, sensorXY, tilts, azimuths, tailScale)
% Draw a marker + boresight arrow for each sensor.
% Tail direction follows azimuth convention (0=+Y, 90=+X, clockwise).
% Tail length = tailScale * sind(tilt), so nadir (0°) has no tail and
% horizon (90°) has the full tailScale length.
hold(ax, 'on');
for ii = 1:size(sensorXY, 1)
x = sensorXY(ii, 1);
y = sensorXY(ii, 2);
if ii == 1
c = [0, 0, 0];
mk = 'o';
else
c = [0.9, 0.2, 0.2];
mk = 'x';
end
scatter(ax, x, y, 80, c, mk, LineWidth=2);
if tilts(ii) > 0
u = tailScale * sind(tilts(ii)) * sind(azimuths(ii));
v = tailScale * sind(tilts(ii)) * cosd(azimuths(ii));
quiver(ax, x, y, u, v, 0, Color=c, LineWidth=2, MaxHeadSize=1.0);
end
end
hold(ax, 'off');
end
-41
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@@ -1,41 +0,0 @@
classdef rfSensor
properties (SetAccess = private, GetAccess = public)
% Physical parameters
c = 3e8; % Speed of light (m/s)
k_B = 1.38e-23 % Boltzmann constant (W/Hz/K) for thermal noise model
T_0 = NaN; % Ambient temperature (Kelvin) for thermal noise model
lossExponent = NaN; % Path loss exponent (2 for free space, up to 6 for the lossiest environments)
% Sensor parameters
P_TX = NaN; % Transmit power (Watts)
BW = NaN; % Bandwidth (Hz)
f_c = NaN; % Center frequency (Hz)
G_RX_dBi = NaN; % Receiver antenna gain
beamwidthExponent = NaN; % Antenna beamwidth exponent for cosine radiation pattern, larger exponent -> narrower beam
% Values computed at initialization
P_TX_dBm = NaN; % Transmit power (dBm)
N = NaN; % Thermal noise
constantGainTerm_dB = NaN; % used in RSS calculation, only need to compute once
% Cached state (per timestep)
end
properties (Access = public)
tilt = NaN; % Antenna boresight tilt (deg): 0=nadir, 90=horizon
azimuth = NaN; % Antenna boresight azimuth (deg): 0=+y, 90=+x, 180=-y, 270=-x
rssCache (:,1) double = double.empty(0,1); % linear-scale RSS to last ground targets grid
end
methods (Access = public)
[obj] = initialize(obj, txPower, temperature, bandwidth, centerFreq, rxGain, beamwidthExponent, tilt, azimuth); % initialize sensor, define parameters
[SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors); % determine sensor performance for a given single sensor and target geometry
[d, dx, dy, dz] = computePointToPoints(obj, agentPos, targetPos);
[value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
[f] = plotParameters(obj); % debug, plot sensor response as a function of distance and tilt angle
[f] = plotPerformance(obj, altitude, otherSensorsPos, otherSensors); % debug, plot SNR or SINR ground heatmap for a given geometry
[f] = plot(obj, altitude, otherSensorsPos, otherSensors);
obj = clearRssCache(obj);
end
methods (Access = private)
x = RSS(obj, d, dx, dy, dz); % Received signal strength (function of distance and tilt angle)
G_TX_dB = transmitterGain(obj, theta); % Antenna gain for a given angle from boresight (degrees)
L_FSPL_dB = pathLoss(obj, d); % Free space path loss for a given TX/RX pair
end
end
-34
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function [SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
agentPos (1, 3) double;
targetPos (:, 3) double;
otherSensorsPos (:, 3) double = [];
otherSensors (:, 1) cell = {};
end
arguments (Output)
SINR (:, 1) double;
SNR (:, 1) double;
obj (1, 1) {mustBeA(obj, "rfSensor")};
otherSensors (:, 1) cell;
end
assert(size(otherSensorsPos, 1) == size(otherSensors, 1), "Mismatch in number of other sensor positions (%d) and number of other sensors (%d) provided", size(otherSensorsPos, 1), size(otherSensors, 1));
if isempty(obj.rssCache)
[d, dx, dy, dz] = obj.computePointToPoints(agentPos, targetPos);
obj.rssCache = 1e-3 .* 10 .^ (0.1 .* obj.RSS(d, dx, dy, dz)); % dBm → W
end
S = obj.rssCache;
I = zeros(size(S));
for ii = 1:size(otherSensors, 1)
if isempty(otherSensors{ii}.rssCache)
[d_o, dx_o, dy_o, dz_o] = otherSensors{ii}.computePointToPoints(otherSensorsPos(ii, 1:3), targetPos);
otherSensors{ii}.rssCache = 1e-3 .* 10 .^ (0.1 .* otherSensors{ii}.RSS(d_o, dx_o, dy_o, dz_o)); % dBm → W
end
I = I + otherSensors{ii}.rssCache;
end
SINR = 10*log10(S ./ (I + obj.N));
SNR = 10*log10(S ./ obj.N);
end
-12
View File
@@ -1,12 +0,0 @@
function value = transmitterGain(obj, theta)
arguments (Input)
obj (1, 1) {mustBeA(obj, "rfSensor")};
theta (:, 1) double; % angle from boresight (degrees)
end
arguments (Output)
value (:, 1) double
end
% Cosine pattern: peak at boresight, -inf dB at 90°.
% Clamped so targets behind the antenna (theta > 90°) get -inf rather than NaN.
value = obj.constantGainTerm_dB + 10 .* obj.beamwidthExponent .* log10(max(0, cosd(theta)));
end
+4 -11
View File
@@ -1,4 +1,4 @@
function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum, objectiveMu, objectiveSigma)
function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum)
arguments (Input)
obj (1,1) {mustBeA(obj, "sensingObjective")};
objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")};
@@ -6,8 +6,6 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
discretizationStep (1, 1) double = 1;
protectedRange (1, 1) double = 1;
sensorPerformanceMinimum (1, 1) double = 1e-6;
objectiveMu (:, 2) double = NaN(1, 2);
objectiveSigma (:, 2, 2) double = NaN(1, 2, 2);
end
arguments (Output)
obj (1,1) {mustBeA(obj, "sensingObjective")};
@@ -39,13 +37,8 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
% store ground position
idx = obj.values == 1;
if any(isnan(objectiveMu))
obj.groundPos = [obj.X(idx), obj.Y(idx)];
obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
else
obj.groundPos = objectiveMu;
end
obj.objectiveSigma = objectiveSigma;
obj.groundPos = [obj.X(idx), obj.Y(idx)];
obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective");
assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
end
+3 -3
View File
@@ -11,16 +11,16 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
% Set random objective position
mu = domain.minCorner;
while domain.distance(mu) < protectedRange * 1.01
while domain.distance(mu) < protectedRange
mu = domain.random();
end
% Set random distribution parameters
sig = reshape([2 + rand * 2, 1; 1, 2 + rand * 2], [1 2 2]);
sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
% Set up random bivariate normal distribution function
objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig);
% Regular initialization
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange, 1e-6, mu(1:2), sig);
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange);
end
+7 -21
View File
@@ -11,39 +11,25 @@ function f = plot(obj, ind, f)
% Create axes if they don't already exist
f = firstPlotSetup(f);
normalized = obj.values ./ sum(obj.values, "all");
cRange = [min(normalized, [], "all"), max(normalized, [], "all")];
% Plot gradient on the "floor" of the domain
if isnan(ind)
ax = f.CurrentAxes;
hold(ax, "on");
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
hold(f.CurrentAxes, "on");
o = surf(f.CurrentAxes, obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
o.HitTest = "off";
o.PickableParts = "none";
clim(ax, cRange);
hold(ax, "off");
hold(f.CurrentAxes, "off");
else
ax = f.Children(1).Children(ind(1));
hold(ax, "on");
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
hold(f.Children(1).Children(ind(1)), "on");
o = surf(f.Children(1).Children(ind(1)), obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
o.HitTest = "off";
o.PickableParts = "none";
clim(ax, cRange);
hold(ax, "off");
hold(f.Children(1).Children(ind(1)), "off");
end
% Add to other perspectives
if size(ind, 2) > 1
for ii = 2:size(ind, 2)
axCopy = f.Children(1).Children(ind(ii));
copyobj(o, axCopy);
% copyobj does not carry color scaling. The objective values are
% sum-normalized (tiny), so without matching CLim the copied surface
% is squished to one color once the destination axes' auto CLim is
% widened by later surfaces (e.g. agent geometries). Pin it to the
% source range so the heatmap renders as a visible gradient.
clim(axCopy, cRange);
copyobj(o, f.Children(1).Children(ind(ii)));
end
end
end
+1 -2
View File
@@ -2,8 +2,7 @@ classdef sensingObjective
% Sensing objective definition parent class
properties (SetAccess = private, GetAccess = public)
label = "";
groundPos = NaN(1, 2);
objectiveSigma = NaN(1, 2, 2);
groundPos = [NaN, NaN];
discretizationStep = NaN;
X = [];
Y = [];
-9
View File
@@ -1,9 +0,0 @@
function value = halfAngle(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, "sigmoidSensor")};
end
arguments (Output)
value (1, 1) double;
end
value = obj.alphaTilt;
end
+1 -8
View File
@@ -1,24 +1,17 @@
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth)
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt)
arguments (Input)
obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
alphaDist (1, 1) double;
betaDist (1, 1) double;
alphaTilt (1, 1) double;
betaTilt (1, 1) double;
tilt (1, 1) double = 0;
azimuth (1, 1) double = 0;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
end
% Sensor performance parameters
obj.alphaDist = alphaDist;
obj.betaDist = betaDist;
obj.alphaTilt = alphaTilt;
obj.betaTilt = betaTilt;
% Sensor pointing parameters
obj.tilt = tilt;
obj.azimuth = azimuth;
end
+5 -31
View File
@@ -1,32 +1,22 @@
function f = plotParameters(obj, f)
function f = plotParameters(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, "sigmoidSensor")};
f (1, 1) {mustBeA(f, "matlab.ui.Figure")} = figure;
end
arguments (Output)
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
end
% Distance and tilt sample points
d = 0:(obj.alphaDist / 200):(2*obj.alphaDist);
t = -90:0.5:90;
d = 0:(obj.alphaDist / 100):(2*obj.alphaDist);
t = -90:1:90;
% Sample membership functions
d_x = obj.distanceMembership(d);
t_x = obj.tiltMembership(t);
% pad ends of sampled results with zeros at +/- some big number
big = 1e6 * max(d);
d = [-big, d, big];
t = [-big, t, big];
d_x = [0, d_x', 0];
t_x = [0, t_x', 0];
% Plot resultant sigmoid curves
hold(gca(f), "on");
if isempty(gca(f).Children)
tiledlayout(f, 2, 1, "TileSpacing", "tight", "Padding", "compact");
end
f = figure;
tiledlayout(f, 2, 1, "TileSpacing", "tight", "Padding", "compact");
% Distance
nexttile(1, [1, 1]);
@@ -34,12 +24,9 @@ function f = plotParameters(obj, f)
title("Distance Membership Sigmoid");
xlabel("Distance (m)");
ylabel("Membership");
ld = legend();
hold("on");
plot(d, d_x, "LineWidth", 2);
hold("off");
xData = cell2mat(arrayfun(@(x) x.XData(2:(end - 1)), f.Children.Children(end).Children, 'UniformOutput', false));
xlim([min(xData, [], "all"), max(xData, [], "all")]);
ylim([0, 1]);
% Tilt
@@ -48,21 +35,8 @@ function f = plotParameters(obj, f)
title("Tilt Membership Sigmoid");
xlabel("Tilt (deg)");
ylabel("Membership");
lt = legend();
hold("on");
plot(t, t_x, "LineWidth", 2);
hold("off");
xlim([-90, 90]);
ylim([0, 1]);
% add legends
nexttile(1, [1, 1]);
f.Children.Children(3).String{end} = sprintf("Sensor %d", length(f.Children.Children(end).Children));
f.Children.Children(1).String{end} = sprintf("Sensor %d", length(f.Children.Children(end).Children));
nexttile(2, [1, 1]);
f.Children.Children(3).String{end} = sprintf("Sensor %d", length(f.Children.Children(end).Children));
f.Children.Children(1).String{end} = sprintf("Sensor %d", length(f.Children.Children(end).Children));
hold(gca(f), "off");
end
+6 -10
View File
@@ -8,20 +8,16 @@ function value = sensorPerformance(obj, agentPos, targetPos)
value (:, 1) double;
end
% Unit vectors from agent to each target
diffs = targetPos - agentPos;
d = vecnorm(diffs, 2, 2);
dirs = diffs ./ d;
% compute direct distance and distance projected onto the ground
d = vecnorm(agentPos - targetPos, 2, 2); % distance from sensor to target
x = vecnorm(agentPos(1:2) - targetPos(:, 1:2), 2, 2); % distance from sensor nadir to target nadir (i.e. distance ignoring height difference)
% Boresight unit vector: tilt=0 → nadir [0,0,-1]; azimuth 0=+Y, 90=+X clockwise
boresight = [sind(obj.tilt)*sind(obj.azimuth), sind(obj.tilt)*cosd(obj.azimuth), -cosd(obj.tilt)];
% Angular offset from boresight to each target direction
angularOffset = acosd(dirs * boresight');
% compute tilt angle
tiltAngle = (180 - atan2d(x, targetPos(:, 3) - agentPos(3))); % degrees
% Membership functions
mu_d = obj.distanceMembership(d);
mu_t = obj.tiltMembership(angularOffset);
mu_t = obj.tiltMembership(tiltAngle);
value = mu_d .* mu_t; % assume pan membership is always 1
end
+5 -11
View File
@@ -6,20 +6,14 @@ classdef sigmoidSensor
alphaTilt = NaN; % degrees
betaTilt = NaN;
end
properties (Access = public)
% pointing states
tilt = 0;
azimuth = 0;
end
methods (Access = public)
[obj] = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth); % initialize sensor, define parameters
[value] = sensorPerformance(obj, agentPos, targetPos); % determine sensor performance for a given single sensor and target geometry
[value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
[f] = plotParameters(obj, f); % debug, plot sensor response as a function of distance and tilt angle
[obj] = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt);
[value] = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos);
[f] = plotParameters(obj);
end
methods (Access = private)
x = distanceMembership(obj, d); % used in computing distance factor of sensor performance
x = tiltMembership(obj, t); % used in computing tilt factor of sensor performance
x = distanceMembership(obj, d);
x = tiltMembership(obj, t);
end
end
-1
View File
@@ -8,6 +8,5 @@ classdef MESSAGE_TYPE < uint8
GUIDANCE_TOGGLE (6) % Server->Client: toggle guidance mode on/off
REQUEST_POSITION (7) % Server->Client: respond with current ENU position
POSITION (8) % Client->Server: current ENU position (3 doubles)
TAKEOFF (9) % Server->Client: take off to 25 m, ACK then READY on arrival
end
end
+1
Submodule aerpaw/aerpawlib added at 705fc699ef.
+7 -32
View File
@@ -44,7 +44,6 @@ class MessageType(IntEnum):
GUIDANCE_TOGGLE = 6
REQUEST_POSITION = 7
POSITION = 8
TAKEOFF = 9
AERPAW_DIR = Path('/root/miSim/aerpaw')
@@ -165,7 +164,7 @@ class UAVRunner(BasicRunner):
# Retry connection up to 10 times (~30 seconds total)
reader, writer = None, None
for attempt in range(100):
for attempt in range(10):
try:
reader, writer = await asyncio.wait_for(
asyncio.open_connection(self.server_ip, self.server_port),
@@ -185,11 +184,13 @@ class UAVRunner(BasicRunner):
log_task = None
nav_task = None
try:
# Takeoff is now driven by a TAKEOFF command from the controller
# (staggered in time between UAVs), not performed at startup. Start
# GPS logging immediately so the ground/idle period is captured too.
# Takeoff to above AERPAW minimum altitude
print("[UAV] Taking off...")
await drone.takeoff(25)
print("[UAV] Takeoff complete, waiting for commands...")
# Start GPS logging in background
log_task = asyncio.create_task(_gps_log_loop(drone))
print("[UAV] Connected; waiting for commands...")
# Command loop - handle all messages from controller
waypoint_num = 0
@@ -212,27 +213,6 @@ class UAVRunner(BasicRunner):
await send_message_type(writer, MessageType.ACK)
print("[UAV] Sent ACK (guidance mode exited, ready for sequential commands)")
elif msg_type == MessageType.TAKEOFF:
# aerpawlib only switches the vehicle to GUIDED inside
# _initialize_postarm(), which await_ready_to_move() runs only
# when the vehicle is DISARMED at the first movement command.
# The safety pilot arms all UAVs at experiment start, so a UAV
# whose takeoff is deliberately delayed (for time separation)
# is already armed by now and would skip that path -> no GUIDED
# switch -> simple_takeoff is ignored in ALT_HOLD and it never
# leaves the ground. Run the post-arm init explicitly to
# guarantee GUIDED mode (and home capture) before taking off;
# takeoff()'s own gate then sees the vehicle armed and does not
# re-initialize.
await send_message_type(writer, MessageType.ACK)
print("[UAV] Sent ACK (takeoff)")
print("[UAV] Initializing (GUIDED) and taking off to 25 m...")
await drone._initialize_postarm()
await drone.takeoff(25)
print("[UAV] Takeoff complete")
await send_message_type(writer, MessageType.READY)
print("[UAV] Sent READY")
elif msg_type == MessageType.REQUEST_POSITION:
# Respond immediately with current ENU position relative to origin
pos = drone.position
@@ -308,11 +288,6 @@ class UAVRunner(BasicRunner):
except (ValueError, asyncio.IncompleteReadError, ConnectionError) as e:
print(f"[UAV] Error: {e}")
except Exception as e:
import traceback
print(f"[UAV] Unhandled exception: {type(e).__name__}: {e}")
traceback.print_exc()
finally:
if nav_task is not None and not nav_task.done():
nav_task.cancel()
+5 -5
View File
@@ -12,8 +12,8 @@ tdm:
# ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
origin:
lat: 35.72595214250436
lon: -78.69917609299937
lat: 35.72550610629396
lon: -78.70019657805574
alt: 0.0 # Alt=0 means ENU z directly becomes target altitude above home
# Environment-specific settings
environments:
@@ -28,11 +28,11 @@ environments:
port: 5000
testbed:
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
mavlink:
ip: "192.168.32.26"
port: 14550
# Controller runs on host machine (192.168.X.1, generally)
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
controller:
ip: "192.168.112.1"
ip: "192.168.122.1"
port: 5000
+5 -5
View File
@@ -12,8 +12,8 @@ tdm:
# ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
origin:
lat: 35.72595214250436
lon: -78.69917609299937
lat: 35.72550610629396
lon: -78.70019657805574
alt: 0.0 # Alt=0 means ENU z directly becomes target altitude above home
# Environment-specific settings
environments:
@@ -28,11 +28,11 @@ environments:
port: 5000
testbed:
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
mavlink:
ip: "192.168.32.26"
port: 14550
# Controller runs on host machine (192.168.X.1, generally)
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
controller:
ip: "192.168.112.1"
ip: "192.168.122.1"
port: 5000
+2 -2
View File
@@ -1,2 +1,2 @@
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology, txPower, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth
1, 80, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "60.0, 80.0, 45.0, 70.0", "70, 15, 15, 20, 20, 15, 15, 70", 0.15, "15.0, 15.0, 50.0, 40.0, 10.0, 45.0", 8, "0.0, 30.0, 0.0, 42.0, 30.0, 0.0, 84.0, 30.0, 0.0, 13.0, 60.0, 0.0, 55.0, 60.0, 0.0, 0.0, 90, 0.0, 42.0, 90.0, 0.0, 84.0, 90.0, 0.0", "16.0, 40.0, 100.0, 58.0, 40.0, 100.0, 100.0, 40.0, 100.0, 29.0, 70.0, 100.0, 71.0, 70.0, 100.0, 16.0, 100.0, 100.0, 58.0, 100.0, 100.0, 100.0, 100.0, 100.0", 0, 2.0, 1, "0.2, 0.1", 0, 5.0, 2.5, 290.0, 2.4e9, 20e6
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax
5, 120, 30.0, 0.1, 1.0, 2.0, 100, 3, "3.0, 3.0", "30.0, 30.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "50.0, 50.0, 80.0", "35.0, 35.0", "10, 5, 5, 10", 0.15, "5.0, 10.0, 45.0, 15.0, 10.0, 35.0", 1, "2.0, 15.0, 0.0", "25.0, 25.0, 50.0"
1 timestep maxIter minAlt discretizationStep protectedRange initialStepSize barrierGain barrierExponent collisionRadius comRange alphaDist betaDist alphaTilt betaTilt domainMin domainMax objectivePos objectiveVar sensorPerformanceMinimum initialPositions numObstacles obstacleMin obstacleMax useDoubleIntegrator dampingCoeff useFixedTopology txPower useSinrComms sinrThreshold pathLossExponent ambientTemp centerFreq bandwidth
2 1 5 80 120 35.0 30.0 0.1 2.0 1.0 6 2.0 1 100 1 3 8.0, 8.0 3.0, 3.0 35.0, 35.0 30.0, 30.0 80.0, 50.0 80.0, 80.0 0.25, 1.0 0.25, 0.25 8.0, 25.0 5.0, 5.0 0.1, 0.02 0.1, 0.1 0.0, 0.0, 0.0 100.0, 100.0, 100.0 50.0, 50.0, 80.0 60.0, 80.0, 45.0, 70.0 35.0, 35.0 70, 15, 15, 20, 20, 15, 15, 70 10, 5, 5, 10 0.15 15.0, 15.0, 50.0, 40.0, 10.0, 45.0 5.0, 10.0, 45.0, 15.0, 10.0, 35.0 8 1 0.0, 30.0, 0.0, 42.0, 30.0, 0.0, 84.0, 30.0, 0.0, 13.0, 60.0, 0.0, 55.0, 60.0, 0.0, 0.0, 90, 0.0, 42.0, 90.0, 0.0, 84.0, 90.0, 0.0 2.0, 15.0, 0.0 16.0, 40.0, 100.0, 58.0, 40.0, 100.0, 100.0, 40.0, 100.0, 29.0, 70.0, 100.0, 71.0, 70.0, 100.0, 16.0, 100.0, 100.0, 58.0, 100.0, 100.0, 100.0, 100.0, 100.0 25.0, 25.0, 50.0 0 2.0 1 0.2, 0.1 0 5.0 2.5 290.0 2.4e9 20e6
-2
View File
@@ -1,2 +0,0 @@
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
1, 80, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "60.0, 80.0, 45.0, 70.0", "70, 15, 15, 20, 20, 15, 15, 70", 0.15, "15.0, 15.0, 50.0, 40.0, 10.0, 45.0", 8, "0.0, 30.0, 0.0, 42.0, 30.0, 0.0, 84.0, 30.0, 0.0, 13.0, 60.0, 0.0, 55.0, 60.0, 0.0, 0.0, 90, 0.0, 42.0, 90.0, 0.0, 84.0, 90.0, 0.0", "16.0, 40.0, 100.0, 58.0, 40.0, 100.0, 100.0, 40.0, 100.0, 29.0, 70.0, 100.0, 71.0, 70.0, 100.0, 16.0, 100.0, 100.0, 58.0, 100.0, 100.0, 100.0, 100.0, 100.0", 0, 2.0, 1
1 timestep maxIter minAlt discretizationStep protectedRange initialStepSize barrierGain barrierExponent collisionRadius comRange alphaDist betaDist alphaTilt betaTilt domainMin domainMax objectivePos objectiveVar sensorPerformanceMinimum initialPositions numObstacles obstacleMin obstacleMax useDoubleIntegrator dampingCoeff useFixedTopology
2 1 80 35.0 0.1 2.0 6 1 1 8.0, 8.0 35.0, 35.0 80.0, 50.0 0.25, 1.0 8.0, 25.0 0.1, 0.02 0.0, 0.0, 0.0 100.0, 100.0, 100.0 60.0, 80.0, 45.0, 70.0 70, 15, 15, 20, 20, 15, 15, 70 0.15 15.0, 15.0, 50.0, 40.0, 10.0, 45.0 8 0.0, 30.0, 0.0, 42.0, 30.0, 0.0, 84.0, 30.0, 0.0, 13.0, 60.0, 0.0, 55.0, 60.0, 0.0, 0.0, 90, 0.0, 42.0, 90.0, 0.0, 84.0, 90.0, 0.0 16.0, 40.0, 100.0, 58.0, 40.0, 100.0, 100.0, 40.0, 100.0, 29.0, 70.0, 100.0, 71.0, 70.0, 100.0, 16.0, 100.0, 100.0, 58.0, 100.0, 100.0, 100.0, 100.0, 100.0 0 2.0 1
-2
View File
@@ -1,2 +0,0 @@
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
1, 125, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "65.0, 15.0, 65.0, 65.0, 15.0, 45.0", 3, "0.0, 25.0, 55.0, 40.0, 10.0, 0.0, 40.0, 45.0, 60.0", "100.0, 70.0, 60.0, 45.0, 80.0, 55.0, 100.0, 50.0, 100.0", 0, 2.0, 1
1 timestep maxIter minAlt discretizationStep protectedRange initialStepSize barrierGain barrierExponent collisionRadius comRange alphaDist betaDist alphaTilt betaTilt domainMin domainMax objectivePos objectiveVar sensorPerformanceMinimum initialPositions numObstacles obstacleMin obstacleMax useDoubleIntegrator dampingCoeff useFixedTopology
2 1 125 35.0 0.1 2.0 6 1 1 8.0, 8.0 35.0, 35.0 80.0, 50.0 0.25, 1.0 8.0, 25.0 0.1, 0.02 0.0, 0.0, 0.0 100.0, 100.0, 100.0 30.0, 80.0 60, 20, 20, 30 0.15 65.0, 15.0, 65.0, 65.0, 15.0, 45.0 3 0.0, 25.0, 55.0, 40.0, 10.0, 0.0, 40.0, 45.0, 60.0 100.0, 70.0, 60.0, 45.0, 80.0, 55.0, 100.0, 50.0, 100.0 0 2.0 1
@@ -1,2 +0,0 @@
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
1, 100, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 80.0", "0.25, 0.25", "8.0, 8.0", "0.1, 0.1", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "66.6, 66.6", "55, 35, 35, 55", 0.15, "15.0, 15.0, 50.0, 40.0, 15.0, 50.0", 1, "0.0, 35.0, 0.0", "50, 40.0, 60", 1, 2.0, 1
1 timestep maxIter minAlt discretizationStep protectedRange initialStepSize barrierGain barrierExponent collisionRadius comRange alphaDist betaDist alphaTilt betaTilt domainMin domainMax objectivePos objectiveVar sensorPerformanceMinimum initialPositions numObstacles obstacleMin obstacleMax useDoubleIntegrator dampingCoeff useFixedTopology
2 1 100 35.0 0.1 2.0 6 1 1 8.0, 8.0 35.0, 35.0 80.0, 80.0 0.25, 0.25 8.0, 8.0 0.1, 0.1 0.0, 0.0, 0.0 100.0, 100.0, 100.0 66.6, 66.6 55, 35, 35, 55 0.15 15.0, 15.0, 50.0, 40.0, 15.0, 50.0 1 0.0, 35.0, 0.0 50, 40.0, 60 1 2.0 1
-2
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@@ -1,2 +0,0 @@
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
1, 125, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "90.0, 10.0, 50.0, 65.0, 15.0, 45.0", 4, "0.0, 30.0, 0.0, 70.0, 30.0, 0.0, 0.0, 60.0, 0.0, 55.0, 60.0, 0.0", "50.0, 40.0, 100.0, 100.0, 40.0, 100.0, 35.0, 70.0, 100.0, 100.0, 70.0, 100.0", 0, 2.0, 1
1 timestep maxIter minAlt discretizationStep protectedRange initialStepSize barrierGain barrierExponent collisionRadius comRange alphaDist betaDist alphaTilt betaTilt domainMin domainMax objectivePos objectiveVar sensorPerformanceMinimum initialPositions numObstacles obstacleMin obstacleMax useDoubleIntegrator dampingCoeff useFixedTopology
2 1 125 35.0 0.1 2.0 6 1 1 8.0, 8.0 35.0, 35.0 80.0, 50.0 0.25, 1.0 8.0, 25.0 0.1, 0.02 0.0, 0.0, 0.0 100.0, 100.0, 100.0 30.0, 80.0 60, 20, 20, 30 0.15 90.0, 10.0, 50.0, 65.0, 15.0, 45.0 4 0.0, 30.0, 0.0, 70.0, 30.0, 0.0, 0.0, 60.0, 0.0, 55.0, 60.0, 0.0 50.0, 40.0, 100.0, 100.0, 40.0, 100.0, 35.0, 70.0, 100.0, 100.0, 70.0, 100.0 0 2.0 1
+288 -168
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File diff suppressed because it is too large. Load diff
+37 -215
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@@ -7,50 +7,34 @@ coder.extrinsic('disp', 'readScenarioCsv');
% Maximum clients supported (one initial position per UAV)
MAX_CLIENTS = 4;
% Three waypoints per UAV: stage (climb) → traverse (XY) → settle (descend)
MAX_TARGETS = MAX_CLIENTS * 3;
% Altitude-staggered flyout/flyback currently supports exactly 2 UAVs
if numClients ~= int32(2)
error('Altitude-staggered flyout/flyback requires exactly 2 UAVs');
end
% Minimum vertical separation maintained between UAVs during XY transit (metres)
TRANSIT_SEP = 30.0;
MAX_TARGETS = MAX_CLIENTS;
% Allocate targets array (MAX_TARGETS x 3)
targets = zeros(MAX_TARGETS, 3);
numWaypoints = int32(0); %#ok<NASGU>
totalLoaded = int32(0);
numWaypoints = int32(0);
totalLoaded = int32(0); % pre-declare type for coder.ceval %#ok<NASGU>
% Experiment start positions from scenario CSV (N x 3)
scenarioPositions = zeros(MAX_CLIENTS, 3);
% Load experiment start positions from scenario CSV
% Load initial UAV positions from scenario CSV
if coder.target('MATLAB')
disp('Loading initial positions from scenario.csv (simulation)...');
tmpSim = miSim;
sc = tmpSim.readScenarioCsv('aerpaw/config/scenario.csv');
flatPos = double(sc.initialPositions); % 1×(3*N) flat vector
posMatrix = reshape(flatPos, 3, [])'; % N×3
posMatrix = reshape(flatPos, 3, [])'; % N×3, same layout as initializeFromCsv
totalLoaded = int32(size(posMatrix, 1));
scenarioPositions(1:totalLoaded, :) = posMatrix;
% MATLAB path: send directly to scenario positions in one waypoint
targets(1:totalLoaded, :) = posMatrix;
numWaypoints = int32(1);
disp(['Loaded ', num2str(double(totalLoaded)), ' initial positions']);
else
coder.cinclude('controller_impl.h');
filename = ['config/scenario.csv', char(0)];
% Load into targets temporarily; copy to scenarioPositions below
totalLoaded = coder.ceval('loadInitialPositions', coder.ref(filename), ...
coder.ref(targets), int32(MAX_TARGETS));
scenarioPositions(1:totalLoaded, :) = targets(1:totalLoaded, :);
numWaypoints = int32(3);
numWaypoints = totalLoaded / int32(numClients);
end
% Load guidance scenario from CSV (parameters for guidance_step)
NUM_SCENARIO_PARAMS = 65;
NUM_SCENARIO_PARAMS = 45;
MAX_OBSTACLES_CTRL = int32(8);
scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
obstacleMin = zeros(MAX_OBSTACLES_CTRL, 3);
@@ -84,126 +68,43 @@ for i = 1:numClients
end
end
% Query takeoff-pad GPS positions before sending any waypoints.
% These are also the flyback targets so each UAV lands where it took off.
initialPositions = zeros(MAX_CLIENTS, 3);
if ~coder.target('MATLAB')
coder.ceval('sendRequestPositions', int32(numClients));
coder.ceval('recvPositions', int32(numClients), coder.ref(initialPositions), int32(MAX_CLIENTS));
else
% Simulation: treat scenario positions as the takeoff locations
initialPositions(1:totalLoaded, :) = scenarioPositions(1:totalLoaded, :);
end
% Waypoint loop: send each waypoint to all clients, wait for all to arrive
for w = 1:numWaypoints
% Send TARGET for waypoint w to each client
for i = 1:numClients
% Targets are grouped by client: client i's waypoints are at rows
% (i-1)*numWaypoints+1 through i*numWaypoints
targetIdx = (i - 1) * numWaypoints + w;
target = targets(targetIdx, :);
% ---- Build altitude-staggered flyout waypoints --------------------------------
% Each UAV follows three phases:
% WP1: Climb to transit altitude at pad XY
% WP2: Traverse to final XY at transit altitude (>= TRANSIT_SEP vertical gap)
% WP3: Descend to final altitude at final XY
%
% Transit altitude assignment: the UAV with the highest final altitude keeps
% that altitude as its transit altitude; the other UAV climbs TRANSIT_SEP above
% it, guaranteeing >= 30 m vertical separation during the simultaneous XY
% traverse (WP2). Both transit altitudes are well above minAlt.
if ~coder.target('MATLAB')
if scenarioPositions(1, 3) >= scenarioPositions(2, 3)
higherIdx = int32(1);
lowerIdx = int32(2);
else
higherIdx = int32(2);
lowerIdx = int32(1);
end
transitAlt = zeros(1, MAX_CLIENTS);
transitAlt(lowerIdx) = scenarioPositions(lowerIdx, 3);
transitAlt(higherIdx) = scenarioPositions(lowerIdx, 3) + TRANSIT_SEP;
for iUAV = 1:numClients
base = double(iUAV - 1) * double(numWaypoints);
targets(base + 1, :) = [initialPositions(iUAV,1), initialPositions(iUAV,2), transitAlt(iUAV)];
targets(base + 2, :) = [scenarioPositions(iUAV,1), scenarioPositions(iUAV,2), transitAlt(iUAV)];
targets(base + 3, :) = scenarioPositions(iUAV, :);
end
end
% -------------------------------------------------------------------------------
% Waypoint loop
if coder.target('MATLAB')
% Simulation: simple lockstep (collisions are not modelled here).
for w = 1:numWaypoints
for i = 1:numClients
targetIdx = (i - 1) * numWaypoints + w;
target = targets(targetIdx, :);
disp(['Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
if coder.target('MATLAB')
disp([datestr(now, 'HH:MM:SS'), ' Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]);
else
coder.ceval('sendTarget', int32(i), coder.ref(target));
end
disp('Waiting for ACK from all clients...');
disp(['All UAVs arrived at waypoint ', num2str(w)]);
end
else
% ---- Staggered flyout -----------------------------------------------------
% Separate the two UAVs in TIME so they are never doing the same vertical
% climb at the same moment over their ~10 m-separated pads (which can trip
% the proximity guard on a spurious GPS sample). The UAV that transits
% highest leads by exactly one event.
%
% Events per UAV: 1 = TAKEOFF (25 m), 2 = WP1 (climb at pad), 3 = WP2
% (traverse), 4 = WP3 (descend). At each step the higher UAV does event
% `step` while the lower UAV does event `step-1`; both are dispatched, then
% we collect ACK and then READY (arrival) from each active UAV.
numEvents = double(numWaypoints) + 1; % 3 waypoints + 1 takeoff
for step = 1:(numEvents + 1)
hEvent = step;
lEvent = step - 1;
hActive = (hEvent >= 1) && (hEvent <= numEvents);
lActive = (lEvent >= 1) && (lEvent <= numEvents);
% --- Dispatch this step's event to each active UAV ---
if hActive
if hEvent == 1
coder.ceval('sendMessageType', higherIdx, int32(MESSAGE_TYPE.TAKEOFF));
else
hRow = (double(higherIdx) - 1) * double(numWaypoints) + (hEvent - 1);
hTarget = targets(hRow, :);
coder.ceval('sendTarget', higherIdx, coder.ref(hTarget));
end
end
if lActive
if lEvent == 1
coder.ceval('sendMessageType', lowerIdx, int32(MESSAGE_TYPE.TAKEOFF));
else
lRow = (double(lowerIdx) - 1) * double(numWaypoints) + (lEvent - 1);
lTarget = targets(lRow, :);
coder.ceval('sendTarget', lowerIdx, coder.ref(lTarget));
end
end
% Wait for ACK from all clients
if coder.target('MATLAB')
disp('Waiting for ACK from all clients...');
else
coder.ceval('waitForAllMessageType', int32(numClients), ...
int32(MESSAGE_TYPE.ACK));
end
% --- Collect ACK (command received) from each active UAV ---
if hActive
coder.ceval('waitForClientMessageType', higherIdx, int32(MESSAGE_TYPE.ACK));
end
if lActive
coder.ceval('waitForClientMessageType', lowerIdx, int32(MESSAGE_TYPE.ACK));
end
% --- Collect READY (arrived at event) from each active UAV ---
if hActive
coder.ceval('waitForClientMessageType', higherIdx, int32(MESSAGE_TYPE.READY));
end
if lActive
coder.ceval('waitForClientMessageType', lowerIdx, int32(MESSAGE_TYPE.READY));
end
% Wait for READY from all clients (all arrived at waypoint w)
if coder.target('MATLAB')
disp(['All UAVs arrived at waypoint ', num2str(w)]);
else
coder.ceval('waitForAllMessageType', int32(numClients), ...
int32(MESSAGE_TYPE.READY));
end
end
% ---- Phase 2: miSim guidance loop ----------------------------------------
% Number of guidance steps comes from maxIter in scenario.csv (scenarioParams(2))
% so the controller and the agent step-decay schedule stay in sync.
if coder.target('MATLAB')
MAX_GUIDANCE_STEPS = int32(sc.maxIter);
else
MAX_GUIDANCE_STEPS = int32(scenarioParams(2));
end
% Guidance parameters (adjust here and recompile as needed)
MAX_GUIDANCE_STEPS = int32(100); % number of guidance iterations
% Enter guidance mode on all clients
if ~coder.target('MATLAB')
@@ -216,18 +117,14 @@ if ~coder.target('MATLAB')
coder.ceval('sendRequestPositions', int32(numClients));
coder.ceval('recvPositions', int32(numClients), coder.ref(positions), int32(MAX_CLIENTS));
else
% Simulation: seed positions from scenario positions so agents don't start at origin
positions(1:totalLoaded, :) = scenarioPositions(1:totalLoaded, :);
% Simulation: seed positions from CSV waypoints so agents don't start at origin
positions(1:totalLoaded, :) = targets(1:totalLoaded, :);
end
guidance_step(positions(1:numClients, :), true, ...
scenarioParams, obstacleMin, obstacleMax, numObstacles);
% Main guidance loop (event-triggered)
for step = 1:MAX_GUIDANCE_STEPS
if ~coder.target('MATLAB')
coder.ceval('setGuidanceStep', int32(step), int32(MAX_GUIDANCE_STEPS));
end
% Run one guidance step: feed current GPS positions in, get targets out
nextPositions = guidance_step(positions(1:numClients, :), false, ...
scenarioParams, obstacleMin, obstacleMax, numObstacles);
@@ -238,7 +135,7 @@ for step = 1:MAX_GUIDANCE_STEPS
if ~coder.target('MATLAB')
coder.ceval('sendTarget', int32(i), coder.ref(target));
else
disp(['[step ', num2str(step), '] target UAV ', num2str(i), ': ', num2str(target)]);
disp([datestr(now, 'HH:MM:SS'), ' [guidance] target UAV ', num2str(i), ': ', num2str(target)]);
end
end
@@ -267,81 +164,6 @@ if ~coder.target('MATLAB')
% last guidance navigation and is back in sequential (ACK/READY) mode.
coder.ceval('waitForAllMessageType', int32(numClients), ...
int32(MESSAGE_TYPE.ACK));
% Reset step counter so post-guidance logging carries no step prefix.
coder.ceval('setGuidanceStep', int32(0), int32(MAX_GUIDANCE_STEPS));
end
% --------------------------------------------------------------------------
% ---- Altitude-staggered flyback -------------------------------------------
% Mirror of flyout: stage (climb) → traverse (XY) → settle (descend to pad).
% Transit altitudes are based on post-guidance positions so the UAV that ended
% higher stays highest, guaranteeing >= TRANSIT_SEP vertical clearance during
% the simultaneous XY traverse.
NUM_RETURN_WP = int32(3);
returnTargets = zeros(MAX_TARGETS, 3);
if ~coder.target('MATLAB')
if positions(1, 3) >= positions(2, 3)
higherRetIdx = int32(1);
lowerRetIdx = int32(2);
else
higherRetIdx = int32(2);
lowerRetIdx = int32(1);
end
returnTransitAlt = zeros(1, MAX_CLIENTS);
returnTransitAlt(lowerRetIdx) = positions(lowerRetIdx, 3);
returnTransitAlt(higherRetIdx) = positions(lowerRetIdx, 3) + TRANSIT_SEP;
for iUAV = 1:numClients
retBase = double(iUAV - 1) * double(NUM_RETURN_WP);
returnTargets(retBase + 1, :) = [positions(iUAV,1), positions(iUAV,2), returnTransitAlt(iUAV)];
returnTargets(retBase + 2, :) = [initialPositions(iUAV,1), initialPositions(iUAV,2), returnTransitAlt(iUAV)];
% Final return waypoint: pad XY from the pre-takeoff GPS query, but a fixed
% 25 m up. That query ran while the UAV was on the ground, so its ENU
% up-component is ~0 (often slightly negative) — using it directly commands
% a negative altitude. RTL/LAND perform the actual touchdown from here.
returnTargets(retBase + 3, :) = [initialPositions(iUAV,1), initialPositions(iUAV,2), 25.0];
end
% Staggered flyback: same higher-leads-by-one pattern as the flyout, but
% over the 3 return waypoints only (the UAVs are already airborne, so there
% is no TAKEOFF event). The higher UAV climbs/traverses/descends one event
% ahead of the lower, so they never share the same descent over their pads.
numReturnEvents = double(NUM_RETURN_WP); % 3
for step = 1:(numReturnEvents + 1)
hEvent = step;
lEvent = step - 1;
hActive = (hEvent >= 1) && (hEvent <= numReturnEvents);
lActive = (lEvent >= 1) && (lEvent <= numReturnEvents);
if hActive
hRow = (double(higherRetIdx) - 1) * double(NUM_RETURN_WP) + hEvent;
hTarget = returnTargets(hRow, :);
coder.ceval('sendTarget', higherRetIdx, coder.ref(hTarget));
end
if lActive
lRow = (double(lowerRetIdx) - 1) * double(NUM_RETURN_WP) + lEvent;
lTarget = returnTargets(lRow, :);
coder.ceval('sendTarget', lowerRetIdx, coder.ref(lTarget));
end
if hActive
coder.ceval('waitForClientMessageType', higherRetIdx, int32(MESSAGE_TYPE.ACK));
end
if lActive
coder.ceval('waitForClientMessageType', lowerRetIdx, int32(MESSAGE_TYPE.ACK));
end
if hActive
coder.ceval('waitForClientMessageType', higherRetIdx, int32(MESSAGE_TYPE.READY));
end
if lActive
coder.ceval('waitForClientMessageType', lowerRetIdx, int32(MESSAGE_TYPE.READY));
end
end
else
disp('Altitude-staggered return (simulation): UAVs commanded back to takeoff positions.');
end
% --------------------------------------------------------------------------
+19 -57
View File
@@ -17,8 +17,7 @@ function nextPositions = guidance_step(currentPositions, isInit, ...
% Flat array of guidance parameters (compiled path).
% On MATLAB path this is ignored; parameters are loaded
% from scenario.csv via initializeFromCsv instead.
% Index mapping (1-based; authoritative map in
% aerpaw/impl/controller_impl.h):
% Index mapping (1-based):
% 1 timestep 9-12 collisionRadius[1:4]
% 2 maxIter 13-16 comRange[1:4]
% 3 minAlt 17-20 alphaDist[1:4]
@@ -27,20 +26,9 @@ function nextPositions = guidance_step(currentPositions, isInit, ...
% 6 initialStepSize 29-32 betaTilt[1:4]
% 7 barrierGain 33-35 domainMin
% 8 barrierExponent 36-38 domainMax
% 39 numObjectiveComponents
% 40-43 objectivePos [x1,y1,x2,y2]
% 44-51 objectiveVar [per component]
% 52 sensorPerformanceMinimum
% 53 useDoubleIntegrator
% 54 dampingCoeff
% 55 useFixedTopology
% 56-59 txPower[1:4]
% 60 useSinrComms
% 61 sinrThreshold (dB)
% 62 pathLossExponent
% 63 ambientTemp (K)
% 64 centerFreq (Hz)
% 65 bandwidth (Hz)
% 39-40 objectivePos
% 41-44 objectiveVar (2x2, col-major)
% 45 sensorPerformanceMinimum
% obstacleMin (MAX_OBSTACLES × 3) double column-major obstacle corners (compiled path)
% obstacleMax (MAX_OBSTACLES × 3) double
% numObstacles (1,1) int32 actual obstacle count
@@ -103,41 +91,26 @@ if isInit
BETA_TILT_VEC = scenarioParams(29:32);
DOMAIN_MIN = scenarioParams(33:35);
DOMAIN_MAX = scenarioParams(36:38);
NUM_OBJ_COMPONENTS = int32(scenarioParams(39));
OBJECTIVE_POS_FLAT = scenarioParams(40:43); % [x1,y1,x2,y2]; zero-padded if N=1
OBJECTIVE_VAR_FLAT = scenarioParams(44:51); % [v11,v12,v21,v22 per component]
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(52);
USE_DOUBLE_INTEGRATOR = logical(scenarioParams(53));
DAMPING_COEFF = scenarioParams(54);
USE_FIXED_TOPOLOGY = logical(scenarioParams(55));
TX_POWER_VEC = scenarioParams(56:59); % per-UAV [1:MAX_CLIENTS] (W)
USE_SINR_COMMS = logical(scenarioParams(60));
SINR_THRESHOLD = scenarioParams(61); % dB
PATH_LOSS_EXPONENT = scenarioParams(62);
AMBIENT_TEMP = scenarioParams(63); % Kelvin
CENTER_FREQ = scenarioParams(64); % Hz
BANDWIDTH = scenarioParams(65); % Hz
OBJECTIVE_GROUND_POS = scenarioParams(39:40);
OBJECTIVE_VAR = reshape(scenarioParams(41:44), 2, 2);
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(45);
% --- Build domain geometry ---
dom = rectangularPrism;
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
% --- Build sensing objective: sum of N bivariate Gaussians (codegen-compatible) ---
% --- Build sensing objective (inline Gaussian; codegen-compatible) ---
dom.objective = sensingObjective;
xGrid = unique([DOMAIN_MIN(1):DISCRETIZATION_STEP:DOMAIN_MAX(1), DOMAIN_MAX(1)]);
yGrid = unique([DOMAIN_MIN(2):DISCRETIZATION_STEP:DOMAIN_MAX(2), DOMAIN_MAX(2)]);
[gridX, gridY] = meshgrid(xGrid, yGrid);
objValues = zeros(size(gridX));
for kk = 1:NUM_OBJ_COMPONENTS
pos_k = OBJECTIVE_POS_FLAT((kk-1)*2+1 : (kk-1)*2+2);
var_k = reshape(OBJECTIVE_VAR_FLAT((kk-1)*4+1 : (kk-1)*4+4), 2, 2);
dx = gridX - pos_k(1);
dy = gridY - pos_k(2);
ov_a = var_k(1,1); ov_b = var_k(1,2);
ov_c = var_k(2,1); ov_d = var_k(2,2);
ov_det = ov_a * ov_d - ov_b * ov_c;
objValues = objValues + exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
end
dx = gridX - OBJECTIVE_GROUND_POS(1);
dy = gridY - OBJECTIVE_GROUND_POS(2);
% Bivariate Gaussian using objectiveVar covariance matrix (avoids inv())
ov_a = OBJECTIVE_VAR(1,1); ov_b = OBJECTIVE_VAR(1,2);
ov_c = OBJECTIVE_VAR(2,1); ov_d = OBJECTIVE_VAR(2,2);
ov_det = ov_a * ov_d - ov_b * ov_c;
objValues = exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
dom.objective = dom.objective.initializeWithValues(objValues, dom, ...
DISCRETIZATION_STEP, PROTECTED_RANGE, SENSOR_PERFORMANCE_MINIMUM);
@@ -157,7 +130,6 @@ if isInit
ag = agent;
ag = ag.initialize(pos, geom, sensor, COMMS_RANGE_VEC(ii), MAX_ITER, ...
INITIAL_STEP_SIZE, sprintf("UAV %d", ii));
ag.txPower = TX_POWER_VEC(ii); % SINR comms model transmit power (W)
agentList{ii} = ag;
end
@@ -174,9 +146,7 @@ if isInit
% --- Initialise simulation (plots and video disabled) ---
sim = miSim;
sim = sim.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY, false, ...
USE_SINR_COMMS, SINR_THRESHOLD, PATH_LOSS_EXPONENT, AMBIENT_TEMP, CENTER_FREQ, BANDWIDTH);
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
end
% On the init call return current positions unchanged
@@ -205,15 +175,8 @@ else
% 2. Advance timestep counter
sim.timestepIndex = sim.timestepIndex + 1;
% 3. Update communications topology (Lesser Neighbour Assignment).
% Refresh the adjacency graph from current positions first so connectivity
% (fixed-radius or SINR) tracks the agents as they move; otherwise the graph
% would be frozen at init on the compiled path (the MATLAB sim refreshes it
% in @miSim/run.m). Skip when topology is fixed.
if ~sim.useFixedTopology
sim = sim.updateAdjacency();
sim = sim.lesserNeighbor();
end
% 3. Update communications topology (Lesser Neighbour Assignment)
sim = sim.lesserNeighbor();
% 4. Compute Voronoi partitioning
sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
@@ -221,8 +184,7 @@ else
% 5. Unconstrained gradient-ascent step for each agent
for ii = 1:size(sim.agents, 1)
sim.agents{ii} = sim.agents{ii}.run(sim.domain, sim.partitioning, ...
sim.timestepIndex, ii, ...
sim.useDoubleIntegrator, sim.dampingCoeff, sim.timestep, sim.optimizeSensorPointing);
sim.timestepIndex, ii, sim.agents);
end
% 6. Apply CBF safety filter (collision / comms / domain constraints via QP)
+33 -213
View File
@@ -16,44 +16,6 @@
static int serverSocket = -1;
static std::vector<int> clientSockets;
static int guidanceStep = 0;
static int guidanceTotalSteps = 0;
static struct timespec lastStepTime = {0, 0};
// During guidance returns "(%d/%d) "; outside guidance returns "HH:MM:SS ".
static std::string logPrefix() {
if (guidanceStep > 0) {
char buf[32];
snprintf(buf, sizeof(buf), "(%d/%d) ", guidanceStep, guidanceTotalSteps);
return std::string(buf);
}
time_t now = time(nullptr);
struct tm* lt = localtime(&now);
char ts[16];
strftime(ts, sizeof(ts), "%H:%M:%S", lt);
return std::string(ts) + " ";
}
void setGuidanceStep(int step, int totalSteps) {
struct timespec now;
clock_gettime(CLOCK_MONOTONIC, &now);
// From step 2 onward, elapsed = setGuidanceStep(N-1) → setGuidanceStep(N),
// which spans the full prior iteration: guidance computation + target send
// + flight + position request/receive.
if (step > 1 && lastStepTime.tv_sec != 0) {
double elapsed = (now.tv_sec - lastStepTime.tv_sec)
+ (now.tv_nsec - lastStepTime.tv_nsec) * 1e-9;
guidanceStep = step;
guidanceTotalSteps = totalSteps;
std::cout << logPrefix() << "Iteration duration: " << elapsed << " s\n";
} else {
guidanceStep = step;
guidanceTotalSteps = totalSteps;
}
lastStepTime = now;
}
void initSockets() {}
void cleanupSockets() {}
@@ -222,13 +184,9 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
// 28-31: betaTilt[1:4]
// 32-34: domainMin (east, north, up)
// 35-37: domainMax (east, north, up)
// 38 : numObjectiveComponents (1 or 2; inferred from objectivePos field length)
// 39-42: objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
// 43-50: objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
// 51 : sensorPerformanceMinimum (CSV column 18)
// 52 : useDoubleIntegrator (CSV column 23)
// 53 : dampingCoeff (CSV column 24)
// 54 : useFixedTopology (CSV column 25)
// 38-39: objectivePos (east, north)
// 40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
// 44 : sensorPerformanceMinimum
// Returns 1 on success, 0 on failure.
int loadScenario(const char* filename, double* params) {
char line[4096];
@@ -238,10 +196,10 @@ int loadScenario(const char* filename, double* params) {
strncpy(copy, line, sizeof(copy) - 1);
copy[sizeof(copy) - 1] = '\0';
char* fields[40];
int nf = splitCSVRow(copy, fields, 40);
if (nf < 26) {
fprintf(stderr, "loadScenario: expected >=26 columns, got %d\n", nf);
char* fields[32];
int nf = splitCSVRow(copy, fields, 32);
if (nf < 19) {
fprintf(stderr, "loadScenario: expected >=19 columns, got %d\n", nf);
return 0;
}
@@ -306,141 +264,34 @@ int loadScenario(const char* filename, double* params) {
}
}
// objectivePos: column 16 — 2 values per component (up to 2 components).
// Infer numObjectiveComponents from the number of values parsed.
// objectivePos: column 16
{
char tmp[256]; strncpy(tmp, fields[16], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
char* t = trimField(tmp);
double posVals[4] = {0, 0, 0, 0};
int posCount = 0;
char* tok = strtok(t, ",");
while (tok && posCount < 4) {
posVals[posCount++] = atof(tok);
tok = strtok(nullptr, ",");
}
// Check for a 5th token — would mean > 2 components
if (tok) {
fprintf(stderr, "loadScenario: at most 2 objective Gaussian components supported (objectivePos has >4 values)\n");
if (sscanf(t, "%lf , %lf", &params[38], &params[39]) != 2) {
fprintf(stderr, "loadScenario: failed to parse objectivePos: %s\n", t);
return 0;
}
if (posCount == 0 || posCount % 2 != 0) {
fprintf(stderr, "loadScenario: objectivePos must have 2 or 4 values, got %d\n", posCount);
return 0;
}
int nObj = posCount / 2;
params[38] = (double)nObj;
for (int k = 0; k < 4; k++) params[39 + k] = posVals[k]; // zero-padded for nObj=1
}
// objectiveVar: column 17 — 4 values per component (v11,v12,v21,v22).
// objectiveVar: column 17, format "v11, v12, v21, v22"
{
char tmp[512]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
char tmp[256]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
char* t = trimField(tmp);
int nObj = (int)params[38];
double varVals[8] = {0, 0, 0, 0, 0, 0, 0, 0};
int varCount = 0;
char* tok = strtok(t, ",");
while (tok && varCount < 8) {
varVals[varCount++] = atof(tok);
tok = strtok(nullptr, ",");
}
if (varCount != nObj * 4) {
fprintf(stderr, "loadScenario: objectiveVar has %d values but expected %d (4 per component)\n",
varCount, nObj * 4);
if (sscanf(t, "%lf , %lf , %lf , %lf", &params[40], &params[41], &params[42], &params[43]) != 4) {
fprintf(stderr, "loadScenario: failed to parse objectiveVar: %s\n", t);
return 0;
}
for (int k = 0; k < 8; k++) params[43 + k] = varVals[k]; // zero-padded for nObj=1
}
// sensorPerformanceMinimum: column 18
{
char tmp[64]; strncpy(tmp, fields[18], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[51] = atof(trimField(tmp));
params[44] = atof(trimField(tmp));
}
// useDoubleIntegrator: column 23
{
char tmp[64]; strncpy(tmp, fields[23], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[52] = atof(trimField(tmp));
}
// dampingCoeff: column 24
{
char tmp[64]; strncpy(tmp, fields[24], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[53] = atof(trimField(tmp));
}
// useFixedTopology: column 25
{
char tmp[64]; strncpy(tmp, fields[25], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[54] = atof(trimField(tmp));
}
// ---- SINR communications model (columns 26–30; optional) ----
// Defaults mirror @miSim/initializeFromCsv.m so a CSV predating the SINR
// model still loads (useSinrComms stays 0 -> fixed-radius path is used).
// txPower[1:4] -> params[55:58]; useSinrComms -> 59;
// sinrThreshold (dB) -> 60; pathLossExponent -> 61; ambientTemp (K) -> 62;
// centerFreq (Hz) -> 63; bandwidth (Hz) -> 64.
params[55] = 0.1; params[56] = 0.1; params[57] = 0.1; params[58] = 0.1;
params[59] = 0.0; // useSinrComms
params[60] = 0.0; // sinrThreshold (dB)
params[61] = 2.0; // pathLossExponent
params[62] = 290.0; // ambientTemp (K)
params[63] = 2.4e9; // centerFreq (Hz)
params[64] = 20e6; // bandwidth (Hz)
// txPower: column 26 (per-UAV, up to MAX_CLIENTS_PER_PARAM values, zero-padded)
if (nf > 26) {
char tmp[256]; strncpy(tmp, fields[26], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
char* t = trimField(tmp);
double vals[4] = {0, 0, 0, 0};
int count = 0;
char* tok = strtok(t, ",");
while (tok && count < MAX_CLIENTS_PER_PARAM) {
vals[count++] = atof(tok);
tok = strtok(nullptr, ",");
}
if (count > 0) {
for (int k = 0; k < MAX_CLIENTS_PER_PARAM; k++) params[55 + k] = vals[k];
}
}
// useSinrComms: column 27
if (nf > 27) {
char tmp[64]; strncpy(tmp, fields[27], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[59] = atof(trimField(tmp));
}
// sinrThreshold: column 28 (dB)
if (nf > 28) {
char tmp[64]; strncpy(tmp, fields[28], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[60] = atof(trimField(tmp));
}
// pathLossExponent: column 29
if (nf > 29) {
char tmp[64]; strncpy(tmp, fields[29], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[61] = atof(trimField(tmp));
}
// ambientTemp: column 30 (K)
if (nf > 30) {
char tmp[64]; strncpy(tmp, fields[30], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[62] = atof(trimField(tmp));
}
// centerFreq: column 31 (Hz)
if (nf > 31) {
char tmp[64]; strncpy(tmp, fields[31], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[63] = atof(trimField(tmp));
}
// bandwidth: column 32 (Hz)
if (nf > 32) {
char tmp[64]; strncpy(tmp, fields[32], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[64] = atof(trimField(tmp));
}
printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g], %d objective component(s)\n",
params[32], params[33], params[34], params[35], params[36], params[37], (int)params[38]);
printf("Comms model: %s (SINR threshold %g dB, path-loss exp %g, T=%g K, f_c=%g Hz, BW=%g Hz)\n",
params[59] != 0.0 ? "SINR" : "fixed-radius", params[60], params[61], params[62], params[63], params[64]);
printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g]\n",
params[32], params[33], params[34], params[35], params[36], params[37]);
return 1;
}
@@ -575,27 +426,22 @@ static const char* messageTypeName(uint8_t msgType) {
case 6: return "GUIDANCE_TOGGLE";
case 7: return "REQUEST_POSITION";
case 8: return "POSITION";
case 9: return "TAKEOFF";
default: return "UNKNOWN";
}
}
// Send a single-byte message type to a client (no logging)
static int sendMessageTypeRaw(int clientId, int msgType) {
// Send a single-byte message type to a client
int sendMessageType(int clientId, int msgType) {
if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0;
uint8_t msg = (uint8_t)msgType;
ssize_t sent = send(clientSockets[clientId - 1], &msg, 1, 0);
if (sent != 1) {
std::cerr << "Send failed for client " << clientId << "\n";
return 0;
}
return 1;
}
// Send a single-byte message type to a client
int sendMessageType(int clientId, int msgType) {
if (!sendMessageTypeRaw(clientId, msgType)) return 0;
std::cout << logPrefix() << "Sent " << messageTypeName((uint8_t)msgType) << " to client " << clientId << "\n";
std::cout << "Sent " << messageTypeName(msg) << " to client " << clientId << "\n";
return 1;
}
@@ -614,7 +460,13 @@ int sendTarget(int clientId, const double* coords) {
return 0;
}
std::cout << logPrefix() << "Sent TARGET to client " << clientId << ": "
// Timestamp
time_t now = time(nullptr);
struct tm* lt = localtime(&now);
char ts[16];
strftime(ts, sizeof(ts), "%H:%M:%S", lt);
std::cout << ts << " Sent TARGET to client " << clientId << ": "
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
return 1;
}
@@ -662,63 +514,31 @@ int waitForAllMessageType(int numClients, int expectedType) {
return 0;
}
std::cout << "Received " << messageTypeName(msgType) << " from client " << (i + 1) << "\n";
if (msgType == expected) {
completed[i] = true;
completedCount++;
} else {
std::cerr << logPrefix() << "Unexpected " << messageTypeName(msgType)
<< " from client " << (i + 1)
<< " (expected " << messageTypeName(expected) << ")\n";
}
}
}
}
std::cout << logPrefix() << "Received " << messageTypeName(expected) << " from all clients\n";
return 1;
}
// Wait for a specific message type from a SINGLE client (blocking).
// Used by the staggered flyout/flyback, where the controller waits on one UAV
// while the other is still flying its own (offset) event. Skips past any
// unexpected byte and returns 0 on disconnect/error, 1 on success.
int waitForClientMessageType(int clientId, int expectedType) {
if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0;
int sock = clientSockets[clientId - 1];
uint8_t expected = (uint8_t)expectedType;
while (true) {
uint8_t msg;
int len = recv(sock, &msg, 1, MSG_WAITALL);
if (len <= 0) {
std::cerr << logPrefix() << "waitForClientMessageType: client " << clientId
<< " disconnected while waiting for " << messageTypeName(expected) << "\n";
return 0;
}
if (msg == expected) {
std::cout << logPrefix() << "Received " << messageTypeName(expected)
<< " from client " << clientId << "\n";
return 1;
}
std::cerr << logPrefix() << "Unexpected " << messageTypeName(msg) << " from client "
<< clientId << " (expected " << messageTypeName(expected) << ")\n";
}
}
// Broadcast GUIDANCE_TOGGLE to all clients
void sendGuidanceToggle(int numClients) {
for (int i = 1; i <= numClients; i++) {
sendMessageTypeRaw(i, 6); // GUIDANCE_TOGGLE = 6
sendMessageType(i, 6); // GUIDANCE_TOGGLE = 6
}
std::cout << logPrefix() << "Sent GUIDANCE_TOGGLE to clients\n";
}
// Send REQUEST_POSITION to all clients
int sendRequestPositions(int numClients) {
for (int i = 1; i <= numClients; i++) {
if (!sendMessageTypeRaw(i, 7)) return 0; // REQUEST_POSITION = 7
if (!sendMessageType(i, 7)) return 0; // REQUEST_POSITION = 7
}
std::cout << logPrefix() << "Sent REQUEST_POSITION to clients\n";
return 1;
}
@@ -753,7 +573,7 @@ int recvPositions(int numClients, double* positions, int maxClients) {
positions[i + 1 * maxClients] = coords[1]; // north (y)
positions[i + 2 * maxClients] = coords[2]; // up (z)
std::cout << logPrefix() << "Position from client " << (i + 1) << ": "
std::cout << "Position from client " << (i + 1) << ": "
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
}
return 1;
+4 -19
View File
@@ -27,21 +27,10 @@ int loadTargets(const char* filename, double* targets, int maxClients);
// 28-31 betaTilt[1:4]
// 32-34 domainMin
// 35-37 domainMax
// 38 numObjectiveComponents (1 or 2; inferred from objectivePos field length)
// 39-42 objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
// 43-50 objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
// 51 sensorPerformanceMinimum
// 52 useDoubleIntegrator (0=single-integrator, 1=double-integrator)
// 53 dampingCoeff
// 54 useFixedTopology (0=dynamic lesser-neighbor, 1=fixed)
// 55-58 txPower[1:4] (per-UAV transmit power, Watts; SINR comms model)
// 59 useSinrComms (0=fixed-radius comms, 1=SINR/path-loss comms)
// 60 sinrThreshold (SINR connectivity/CBF threshold, dB)
// 61 pathLossExponent (path-loss exponent n)
// 62 ambientTemp (ambient temperature, K; thermal noise)
// 63 centerFreq (carrier frequency, Hz; path-loss offset)
// 64 bandwidth (channel bandwidth, Hz; thermal noise)
#define NUM_SCENARIO_PARAMS 65
// 38-39 objectivePos
// 40-43 objectiveVar (2x2 col-major)
// 44 sensorPerformanceMinimum
#define NUM_SCENARIO_PARAMS 45
#define MAX_CLIENTS_PER_PARAM 4
// Maximum number of obstacles (upper bound for pre-allocated arrays).
#define MAX_OBSTACLES 8
@@ -68,12 +57,8 @@ int loadObstacles(const char* filename,
int sendMessageType(int clientId, int msgType);
int sendTarget(int clientId, const double* coords);
int waitForAllMessageType(int numClients, int expectedType);
// Block until a SINGLE client sends expectedType (used by the staggered
// flyout/flyback to wait on one UAV while the other is mid-flight).
int waitForClientMessageType(int clientId, int expectedType);
// Guidance loop operations
void setGuidanceStep(int step, int totalSteps); // call at the top of each guidance iteration
void sendGuidanceToggle(int numClients);
int sendRequestPositions(int numClients);
int recvPositions(int numClients, double* positions, int maxClients); // column-major maxClients x 3
+4 -9
View File
@@ -3,15 +3,10 @@
#include "controller_impl.h" // TCP implementation header
int main() {
// Derive numClients from initialPositions in scenario.csv
double targets[MAX_CLIENTS_PER_PARAM * 3];
int numClients = loadInitialPositions("config/scenario.csv",
targets, MAX_CLIENTS_PER_PARAM);
if (numClients < 1) {
std::cerr << "Failed to parse numClients from scenario.csv\n";
return 1;
}
std::cout << "Parsed " << numClients << " UAV(s) from scenario.csv\n";
// Number of clients to handle
int numClients = 2; // for now
std::cout << "Initializing TCP server...\n";
// Call MATLAB-generated server function
controller(numClients);
-25
View File
@@ -267,10 +267,6 @@ class CSwSNRRX(gr.top_block):
'/root/Quality', num_uavs, slot_duration, guard_interval)
self.blocks_file_sink_0 = TdmTaggedFileSink(
'/root/Power', num_uavs, slot_duration, guard_interval)
self.blocks_file_sink_noisefloor = TdmTaggedFileSink(
'/root/NoiseFloor', num_uavs, slot_duration, guard_interval)
self._freqoffset_file = open('/root/FreqOffset', 'w')
self._freqoffset_file.write('tx_uav_id,value\n')
self.blocks_divide_xx_0 = blocks.divide_ff(1)
self.blocks_complex_to_real_0_0 = blocks.complex_to_real(1)
self.blocks_complex_to_real_0 = blocks.complex_to_real(1)
@@ -314,7 +310,6 @@ class CSwSNRRX(gr.top_block):
self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_add_const_vxx_0, 0))
self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_sub_xx_0, 0))
self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_sub_xx_0, 1))
self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_file_sink_noisefloor, 0))
self.connect((self.blocks_stream_to_vector_0_0, 0), (self.epy_block_0, 0))
self.connect((self.blocks_sub_xx_0, 0), (self.blocks_file_sink_0_0_0, 0))
self.connect((self.blocks_vector_to_stream_0_0, 0), (self.blocks_keep_m_in_n_0, 0))
@@ -326,26 +321,6 @@ class CSwSNRRX(gr.top_block):
self.connect((self.freq_xlating_fft_filter_ccc_0_0, 0), (self.blocks_stream_to_vector_0_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.blocks_multiply_xx_0, 0))
##################################################
# Frequency offset polling thread
##################################################
def _freq_offset_probe():
frame_dur = slot_duration * num_uavs
while True:
val = self.digital_fll_band_edge_cc_0_0.get_frequency()
freq_hz = val * samp_rate / (2 * math.pi)
now = time.time()
slot_time = now % frame_dur
current_slot = int(slot_time / slot_duration)
time_into_slot = slot_time - current_slot * slot_duration
tx_id = -1 if time_into_slot < guard_interval else current_slot
self._freqoffset_file.write(f'{tx_id},{freq_hz}\n')
self._freqoffset_file.flush()
time.sleep(0.01)
_freq_offset_thread = threading.Thread(target=_freq_offset_probe)
_freq_offset_thread.daemon = True
_freq_offset_thread.start()
def get_args(self):
return self.args
+1 -1
View File
@@ -20,4 +20,4 @@ else
fi
cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS
+1 -1
View File
@@ -20,4 +20,4 @@ else
fi
cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS
+1 -10
View File
@@ -1,16 +1,7 @@
#!/bin/bash
# Drop in replacements for channel sounder scripts
cp startchannelsounderRXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
cp startchannelsounderTXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
cp CSwSNRRX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
# Replace start scripts
cp ../scripts/startexperiment.sh /root/.
cp ../scripts/startRadio.sh /root/Profiles/ProfileScripts/Radio/.
cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"
echo "REMEMBER! Manually copy startVehicle_controller.sh to ~/Profiles/ProfileScripts/Vehicle/startVehicle.sh on the fixed node"
-28
View File
@@ -1,28 +0,0 @@
function controller = controllerAnalysis(resultsPath)
arguments (Input)
resultsPath (1, 1) string;
end
arguments (Output)
controller table;
end
% Measure intervals between issuing commands from the controller
% (make sure this is ~4-5 seconds at minimum to avoid overwhelming the UAV autopilot)
r = dir(resultsPath);
controllerPath = fullfile(r(startsWith({r.name}, 'controller_')).folder, r(startsWith({r.name}, 'controller_')).name);
controllerPath = dir(controllerPath);
controllerPath = fullfile(controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).folder, controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).name);
controller = readControllerLogs(controllerPath);
rpIdx = startsWith(controller.message, "Iteration duration: ");
s = split(controller.message(rpIdx), "Iteration duration: ");
s = split(s(:, 2), ' s');
s = duration(strcat("00:", s(:, 1)), "InputFormat", "mm:ss.SSS");
s.Format = "mm:ss.SSS";
fprintf("Minimum command spacing: %2.3f seconds\n", seconds(min(s)));
fprintf("Maximum command spacing: %2.3f seconds\n", seconds(max(s)));
fprintf("Mean command spacing: %2.3f seconds\n", seconds(mean(s)));
fprintf("Median command spacing: %2.3f seconds\n", seconds(median(s)));
if seconds(min(s)) < 4
warning("Minimum command spacing %2.3f questionably short for AERPAW", seconds(min(s)));
end
end
+5 -41
View File
@@ -1,8 +1,7 @@
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
arguments (Input)
logDirs (1, 1) string;
seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
plotWholeFlight (1, 1) logical = false;
end
arguments (Output)
f (1, 1) matlab.ui.Figure;
@@ -29,7 +28,6 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
logDirs = dir(logDirs);
logDirs = logDirs(3:end);
logDirs = logDirs([logDirs.isdir] == 1);
logDirs = logDirs(~startsWith({logDirs.name}, "controller_"));
G = cell(size(logDirs));
for ii = 1:size(logDirs, 1)
@@ -50,10 +48,8 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
% % Plot whole flight, including setup/cleanup
if plotWholeFlight
startIdx = 1;
stopIdx = length(verticalSpeed);
end
% startIdx = 1;
% stopIdx = length(verticalSpeed);
% Convert LLA trajectory data to ENU for external analysis
% NaN out entries outside the algorithm flight range so they don't plot
@@ -62,36 +58,9 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
G{ii} = [G{ii}, enu];
% Do crude comparison of pairwise distances between this UAV and
% all previous UAVs
for jj = 1:(ii - 1)
Ai = G{ii}(:, [1, end-2:end]);
Aj = G{jj}(:, [1, end-2:end]);
% Trim data to match sizes
idx = min([size(Ai, 1), size(Aj, 1)]);
Ai = Ai(1:idx, :); Aj = Aj(1:idx, :);
pos_i = [Ai.East, Ai.North, Ai.Up];
pos_j = [Aj.East, Aj.North, Aj.Up];
d = vecnorm(pos_i - pos_j, 2, 2);
d = d(~isnan(d));
fprintf("Minimum distance between agents %d and %d is %2.3f\n", ii, jj, min(d));
figure;
plot(G{1}.Timestamp(1:length(d)), d);
xlabel("Time"); ylabel("Distance"); title("UAV0 and UAV1 distance"); grid("on");
fprintf("Average distance between agents %d and %d is %2.3f\n", ii, jj, mean(d));
fprintf("Median distance between agents %d and %d is %2.3f\n", ii, jj, median(d));
if min(d) < 6
warning("Minimum distance between agents %d and %d of %2.3f is questionable for AERPAW", ii, jj, min(d));
end
end
% Plot recorded trajectory over specified range of indices
geoplot3(gf, G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx) + seaToGroundLevel, c(mod(ii, length(c))), 'LineWidth', 2, "MarkerSize", 5);
end
fprintf("Flight duration is %s\n", string(G{1}.Timestamp(end) - G{1}.Timestamp(1), 'mm:ss'));
% Plot domain
altOffset = 1; % to avoid clipping into the ground when displayed
@@ -108,14 +77,9 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(1, 3) + altOffset + floorAlt, 1, 5), 'LineWidth', 3, 'Color', 'r');
% Plot objective
if length(params.objectivePos) > 2
objectivePos = reshape(params.objectivePos, [2, length(params.objectivePos) / 2])';
end
objectivePos = [objectivePos, zeros(size(objectivePos, 1), 1)];
objectivePos = [params.objectivePos, 0];
llaObj = enu2lla(objectivePos, lla0, "flat");
for ii = 1:size(llaObj, 1)
geoplot3(gf, [llaObj(ii, 1), llaObj(ii, 1)], [llaObj(ii, 2), llaObj(ii, 2)], [llaObj(ii, 3), domain(2, 3)], 'LineWidth', 3, "Color", 'y');
end
geoplot3(gf, [llaObj(1), llaObj(1)], [llaObj(2), llaObj(2)], [llaObj(3), domain(2, 3)], 'LineWidth', 3, "Color", 'y');
% Plot obstacles
for ii = 1:params.numObstacles
+9 -193
View File
@@ -1,12 +1,9 @@
function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
function [f, R] = plotRadioLogs(resultsPath)
arguments (Input)
resultsPath (1, 1) string;
G cell = {};
tLim (1, 2) datetime = [datetime(-Inf, 'ConvertFrom', 'datenum'), datetime(Inf, 'ConvertFrom', 'datenum')];
end
arguments (Output)
f (1, 1) matlab.ui.Figure;
fDist (1, 1) matlab.ui.Figure;
R cell;
end
@@ -27,60 +24,18 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
R{ii}(bad, :) = [];
end
% Compute path loss from Power (post-processing)
% Power = 20*log10(peak_mag) - rxGain; path loss = txGain - rxGain - Power
txGain_dB = 76; % from startchannelsounderTXGRC.sh GAIN_TX
rxGain_dB = 30; % from startchannelsounderRXGRC.sh GAIN_RX
for ii = 1:numel(R)
R{ii}.PathLoss = txGain_dB - rxGain_dB - R{ii}.Power;
R{ii}.FreqOffset = R{ii}.FreqOffset / 1e6; % Hz to MHz
end
% Build legend labels and color map for up to 4 UAVs
nUAV = numel(R);
colors = lines(nUAV * nUAV);
styles = ["-o", "-s", "-^", "-d", "-v", "-p", "-h", "-<", "->", "-+", "-x", "-*"];
metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
yLabels = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
nMetrics = numel(metricNames);
metricNames = ["SNR", "Power", "Quality"];
yLabels = ["SNR (dB)", "Power (dB)", "Quality"];
% --- Time-based figure ---
f = figure;
tl = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
tl = tiledlayout(3, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
% Distance vs time tile (first)
ax = nexttile(tl);
hold(ax, 'on'); grid(ax, 'on');
legendEntries = string.empty;
ci = 1;
if ~isempty(G)
for rxIdx = 1:nUAV
tbl = R{rxIdx};
txIDs = unique(tbl.TxUAVID);
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
if isempty(rows), continue; end
[~, ia] = unique(rows.Timestamp);
[radioPt, dist] = pairDist(rows(ia, :), G);
if isempty(dist) || all(isnan(dist)), continue; end
valid = ~isnan(dist);
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
end
ylabel(ax, 'Distance (m)');
xlabel(ax, 'Time');
legend(ax, legendEntries, 'Location', 'best');
hold(ax, 'off');
for mi = 1:nMetrics
for mi = 1:numel(metricNames)
ax = nexttile(tl);
hold(ax, 'on');
grid(ax, 'on');
@@ -93,32 +48,23 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
vals = rows.(metricNames(mi));
valid = ~isnan(vals);
rows = rows(valid, :);
vals = vals(valid);
if isempty(rows)
% Skip if all NaN for this metric
if all(isnan(vals))
continue;
end
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, rows.Timestamp, vals, styles(si), ...
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, tbl.RxUAVID(1)); %#ok<AGROW>
% Median per 1/3-second time bin
[t_med, v_med] = timeBinMedian(posixtime(rows.Timestamp), vals, 1/3);
plot(ax, datetime(t_med, 'ConvertFrom', 'posixtime'), v_med, '-', ...
'Color', 'r', 'LineWidth', 2);
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, tbl.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, yLabels(mi));
if mi == nMetrics
if mi == numel(metricNames)
xlabel(ax, 'Time');
end
legend(ax, legendEntries, 'Location', 'best');
@@ -126,134 +72,4 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
end
title(tl, 'Radio Channel Metrics');
% --- Distance-based figure ---
fDist = figure;
if isempty(G)
return;
end
tl2 = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
% Distance vs time tile (first)
ax = nexttile(tl2);
hold(ax, 'on'); grid(ax, 'on');
legendEntries = string.empty;
ci = 1;
for rxIdx = 1:nUAV
tbl = R{rxIdx};
txIDs = unique(tbl.TxUAVID);
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
if isempty(rows), continue; end
[~, ia] = unique(rows.Timestamp);
[radioPt, dist] = pairDist(rows(ia, :), G);
if isempty(dist) || all(isnan(dist)), continue; end
valid = ~isnan(dist);
si = mod(ci - 1, numel(styles)) + 1;
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, 'Distance (m)');
xlabel(ax, 'Time');
legend(ax, legendEntries, 'Location', 'best');
hold(ax, 'off');
for mi = 1:nMetrics
ax = nexttile(tl2);
hold(ax, 'on');
grid(ax, 'on');
legendEntries = string.empty;
ci = 1;
for rxIdx = 1:nUAV
tbl = R{rxIdx};
txIDs = unique(tbl.TxUAVID);
for ti = 1:numel(txIDs)
txID = txIDs(ti);
rows = tbl(tbl.TxUAVID == txID, :);
if isempty(rows)
continue;
end
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
if isempty(rows)
continue;
end
vals = rows.(metricNames(mi));
valid = ~isnan(vals);
rows = rows(valid, :);
vals = vals(valid);
if isempty(rows)
continue;
end
[radioPt, dist] = pairDist(rows, G);
if isempty(dist) || all(isnan(dist)), continue; end
% Drop points where GPS interpolation returned NaN
validDist = ~isnan(dist);
rowTs = radioPt(validDist);
dist = dist(validDist);
vals = vals(validDist);
si = mod(ci - 1, numel(styles)) + 1;
scatter(ax, dist, vals, 9, colors(ci, :), strrep(styles(si), "-", ""), 'filled');
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
% Median per 1/3-second time bin, plotted against median distance
[~, dv_med] = timeBinMedian(rowTs, [dist, vals], 1/3);
[d_med, si_sort] = sort(dv_med(:, 1));
v_med = dv_med(si_sort, 2);
plot(ax, d_med, v_med, '-', 'Color', 'r', 'LineWidth', 2);
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, rows.RxUAVID(1)); %#ok<AGROW>
ci = ci + 1;
end
end
ylabel(ax, yLabels(mi));
if mi == nMetrics
xlabel(ax, 'Distance (m)');
end
legend(ax, legendEntries, 'Location', 'best');
hold(ax, 'off');
end
title(tl2, 'Radio Channel Metrics vs Distance');
end
function [radioPt, dist] = pairDist(rows, G)
% Interpolate GPS-based inter-UAV distance at each row's timestamp.
radioPt = []; dist = [];
txGpsIdx = double(rows.TxUAVID(1)) + 1;
rxGpsIdx = double(rows.RxUAVID(1)) + 1;
if txGpsIdx > numel(G) || rxGpsIdx > numel(G), return; end
Gtx = G{txGpsIdx};
Grx = G{rxGpsIdx};
if ~ismember('East', Gtx.Properties.VariableNames) || ...
~ismember('East', Grx.Properties.VariableNames), return; end
txTs = Gtx.Timestamp; txTs.TimeZone = '';
rxTs = Grx.Timestamp; rxTs.TimeZone = '';
txPt = posixtime(txTs);
rxPt = posixtime(rxTs);
radioPt = posixtime(rows.Timestamp);
validTx = ~isnan(Gtx.East);
validRx = ~isnan(Grx.East);
txE = interp1(txPt(validTx), Gtx.East(validTx), radioPt, 'linear', NaN);
txN = interp1(txPt(validTx), Gtx.North(validTx), radioPt, 'linear', NaN);
txU = interp1(txPt(validTx), Gtx.Up(validTx), radioPt, 'linear', NaN);
rxE = interp1(rxPt(validRx), Grx.East(validRx), radioPt, 'linear', NaN);
rxN = interp1(rxPt(validRx), Grx.North(validRx), radioPt, 'linear', NaN);
rxU = interp1(rxPt(validRx), Grx.Up(validRx), radioPt, 'linear', NaN);
dist = vecnorm([txE - rxE, txN - rxN, txU - rxU], 2, 2);
end
-32
View File
@@ -1,32 +0,0 @@
function T2 = readControllerLogs(filepath)
arguments (Input)
filepath (1, 1) string;
end
arguments (Output)
T2 table;
end
assert(isfile(filepath), "File not found at %s", filepath);
T = readtable(filepath, 'VariableNamingRule', 'preserve');
s = split(T.(T.Properties.VariableNames{1}), ']');
s2 = strip(s(startsWith(s(:, 2), " ("), 1), 'left', '[');
d = datetime(s2, "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS")';
it = s(startsWith(s(:, 2), " ("), 2);
it = str2double(strip(strip(it, 'left'), 'left', '('));
T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", T.Var7));
T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = [];
msg = T.(T.Properties.VariableNames{2});
msg = msg(startsWith(s(:, 2), " ("), :);
s3 = split(msg, ') ');
s3 = s3(:, 2);
msg = append(s3, T.Var3(startsWith(s(:, 2), " (")));
T2 = table(it, d', msg, 'VariableNames', ["iteration", "timestamp", "message"]);
% T.Var1 = datetime(strip(strip(append(T.Var1, " ", T.Var2), 'left', '['), 'right', ']'), "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS");
% T.Var2 = [];
% T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", string(T.Var7), " ", T.Var8, " ", T.Var9));
% T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = []; T.Var8 = []; T.Var9 = [];
% T.Properties.VariableNames{1} = 'timestamp';
% T.Properties.VariableNames{2} = 'message';
% T(ismissing(T.message), :) = [];
end
+14 -61
View File
@@ -2,20 +2,21 @@ function R = readRadioLogs(logPath)
arguments (Input)
logPath (1, 1) string {isfolder(logPath)};
end
arguments (Output)
R (:, 8) table;
R (:, 6) table;
end
% Extract receiving UAV ID from directory name (e.g. "uav0_..." → 0)
[~, dirName] = fileparts(logPath);
rxID = int32(sscanf(dirName, 'uav%d'));
metrics = ["quality", "snr", "power", "noisefloor", "freqoffset"];
metrics = ["quality", "snr", "power"];
logs = dir(logPath);
logs = logs(endsWith({logs(:).name}, metrics + "_log.txt"));
R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), ...
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), ...
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
for ii = 1:numel(logs)
filepath = fullfile(logs(ii).folder, logs(ii).name);
@@ -30,39 +31,25 @@ function R = readRadioLogs(logPath)
end
fid = fopen(filepath, 'r');
% Skip header lines: some files have 2 tail-error lines + 1 column
% header ("tx_uav_id,value"), others start with data immediately.
% Read until a line that looks like a data record, then rewind to it.
dataPattern = '^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+\] [-\d]';
linePos = ftell(fid);
while true
line = fgetl(fid);
if ~ischar(line)
break; % EOF
end
if ~isempty(regexp(line, dataPattern, 'once'))
fseek(fid, linePos, 'bof'); % rewind to start of this line
break;
end
linePos = ftell(fid);
% Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value)
for k = 1:3
fgetl(fid);
end
data = textscan(fid, '[%26c] %d,%f');
fclose(fid);
ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
ts = datetime(data{1}, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
txId = int32(data{2});
val = data{3};
n = numel(ts);
t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), ...
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), ...
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
switch metric
case "snr", t.SNR = val;
case "power", t.Power = val;
case "quality", t.Quality = val;
case "noisefloor", t.NoiseFloor = val;
case "freqoffset", t.FreqOffset = val;
case "snr", t.SNR = val;
case "power", t.Power = val;
case "quality", t.Quality = val;
end
R = [R; t]; %#ok<AGROW>
@@ -70,40 +57,6 @@ function R = readRadioLogs(logPath)
R = sortrows(R, "Timestamp");
% Reconstruct per-measurement timestamps within GNURadio processing batches.
% The flowgraph accumulates one full PN sequence (4095 chips at samp_rate/sps)
% per measurement, but outputs the whole batch simultaneously with a single
% wall-clock timestamp. We reassign timestamps by counting backward from the
% batch processing time at the known PN period interval.
pn_period = 4095 / (2e6 / 16); % 32.76 ms per PN correlation period
for txId = unique(R.TxUAVID)'
rows = find(R.TxUAVID == txId);
if numel(rows) < 2, continue; end
dt = seconds(diff(R.Timestamp(rows)));
break_pos = [1; find(dt > 0.5) + 1];
end_pos = [break_pos(2:end) - 1; numel(rows)];
for b = 1:numel(break_pos)
idx = rows(break_pos(b) : end_pos(b));
batch_ts = posixtime(R.Timestamp(idx));
t_ref = max(batch_ts);
% Multiple metric files share the same processing timestamp for
% each PN period, so group by unique original timestamp rather
% than treating every row as a separate PN period.
[~, ~, group_id] = unique(batch_ts);
n_groups = max(group_id);
new_ts = t_ref - (n_groups - 1 : -1 : 0)' * pn_period;
for g = 1:n_groups
R.Timestamp(idx(group_id == g)) = ...
datetime(new_ts(g), 'ConvertFrom', 'posixtime');
end
end
end
% Remove rows during defined guard period between TDM shifts
R(R.TxUAVID == -1, :) = [];
+9 -42
View File
@@ -1,16 +1,12 @@
%% Plot AERPAW logs (trajectory, radio)
resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "columns_simulated"); % Define path to results copied from AERPAW platform
% Check timeline in controller logs
controller = controllerAnalysis(resultsPath);
resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "t1"); % Define path to results copied from AERPAW platform
% Plot GPS logged data and scenario information (domain, objective, obstacles)
seaToGroundLevel = 110; % measured approximately from USGS national map viewer
plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
% Plot radio statistics (time-based and distance-based)
[fRadio, fRadioDist, R] = plotRadioLogs(resultsPath, G, controller.timestamp([1, end]));
% Plot radio statistics
[fRadio, R] = plotRadioLogs(resultsPath);
%% Run simulation
% Run miSim using same AERPAW scenario definition CSV
@@ -25,14 +21,7 @@ makeVideo = true;
% Define scenario according to CSV specification
domain = rectangularPrism;
domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
if length(params.objectiveVar) > 4 && length(params.objectivePos) > 2
objectiveSigma = permute(reshape(params.objectiveVar, [length(params.objectiveVar)/4 2 2]), [3 1 2]);
objectivePos = reshape(params.objectivePos, [length(params.objectivePos)/2, 2])';
else
objectiveSigma = reshape(params.objectiveVar, [1, 2, 2]);
objectivePos = params.objectivePos;
end
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(objectivePos, objectiveSigma), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
agents = cell(size(params.initialPositions, 2) / 3, 1);
for ii = 1:size(agents, 1)
@@ -44,10 +33,7 @@ for ii = 1:size(agents, 1)
collisionGeometry = spherical;
collisionGeometry = collisionGeometry.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), params.collisionRadius(ii), REGION_TYPE.COLLISION, sprintf("Agent %d collision geometry", ii));
agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, 5.0, sprintf("Agent %d", ii), plotCommsGeometry);
if isfield(params, 'txPower')
agents{ii}.txPower = params.txPower(ii); % SINR comms model transmit power (W)
end
agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, sprintf("Agent %d", ii), plotCommsGeometry);
end
% Create obstacles
@@ -57,22 +43,9 @@ for ii = 1:size(obstacles, 1)
obstacles{ii} = obstacles{ii}.initialize([params.obstacleMin((((ii - 1) * 3) + 1):(ii * 3)); params.obstacleMax((((ii - 1) * 3) + 1):(ii * 3))], "OBSTACLE", sprintf("Obstacle %d", ii));
end
% SINR communications model parameters (optional CSV columns; default to the
% fixed-radius path so existing scenarios are unaffected)
if isfield(params, 'useSinrComms'); useSinrComms = logical(params.useSinrComms); else; useSinrComms = false; end
if isfield(params, 'sinrThreshold'); sinrThreshold = params.sinrThreshold; else; sinrThreshold = 0; end
if isfield(params, 'pathLossExponent'); pathLossExponent = params.pathLossExponent; else; pathLossExponent = 2.0; end
if isfield(params, 'ambientTemp'); ambientTemp = params.ambientTemp; else; ambientTemp = 290.0; end
if isfield(params, 'centerFreq'); centerFreq = params.centerFreq; else; centerFreq = 2.4e9; end
if isfield(params, 'bandwidth'); bandwidth = params.bandwidth; else; bandwidth = 20e6; end
% Set up simulation. The four args after makeVideo (useDoubleIntegrator,
% dampingCoeff, useFixedTopology, optimizeSensorPointing) are kept at their
% prior effective defaults to preserve existing analysis behavior; only the
% SINR comms parameters are threaded through from the scenario.
% Set up simulation
sim = miSim;
sim = sim.initialize(domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, makePlots, makeVideo, ...
false, 2.0, false, false, useSinrComms, sinrThreshold, pathLossExponent, ambientTemp, centerFreq, bandwidth);
sim = sim.initialize(domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, makePlots, makeVideo);
% Save simulation parameters to output file
sim.writeInits();
@@ -80,9 +53,6 @@ sim.writeInits();
% Run
sim = sim.run();
% Save results
sim = sim.teardown();
%% Plot AERPAW trajectory logs onto simulated result for comparison
% Duplicate plot to overlay with logged trajectories
comparison = figure;
@@ -90,12 +60,9 @@ copyobj(sim.f.Children, comparison);
% Plot trajectories on top
for ii = 1:size(G, 1)
gpsTimes = G{ii}.Timestamp;
gpsTimes.TimeZone = '';
inRange = gpsTimes >= controller.timestamp(1) & gpsTimes <= controller.timestamp(end);
for jj = 1:size(sim.spatialPlotIndices, 2)
hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "on");
plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East(inRange), G{ii}.North(inRange), G{ii}.Up(inRange) + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East, G{ii}.North, G{ii}.Up + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "off");
end
end
-29
View File
@@ -1,29 +0,0 @@
function [t_med, v_med] = timeBinMedian(t, v, binWidth)
% Compute median of each column of v within fixed-width time bins.
%
% t - (N,1) posixtime values
% v - (N,K) data matrix; one column per quantity
% binWidth - scalar bin width in seconds
%
% t_med - (B,1) median time of each non-empty bin
% v_med - (B,K) median of each column per non-empty bin
edges = (floor(min(t) / binWidth) * binWidth) : binWidth : ...
(floor(max(t) / binWidth) * binWidth + binWidth);
bins = discretize(t, edges);
nBins = numel(edges) - 1;
K = size(v, 2);
t_all = NaN(nBins, 1);
v_all = NaN(nBins, K);
for bi = 1:nBins
mask = bins == bi;
if ~any(mask), continue; end
t_all(bi) = median(t(mask));
v_all(bi,:) = median(v(mask,:), 1);
end
ok = ~isnan(t_all);
t_med = t_all(ok);
v_med = v_all(ok, :);
end
+3 -3
View File
@@ -32,8 +32,8 @@ else
exit 1
fi
# Client config file: 2nd argument > AERPAW_CLIENT_CONFIG env var > default
CONFIG_FILE="${2:-${AERPAW_CLIENT_CONFIG:-config/client.yaml}}"
# Client config file (optional 2nd argument)
CONFIG_FILE="${2:-config/client.yaml}"
if [ ! -f "$CONFIG_FILE" ]; then
echo "Error: Config file not found: $CONFIG_FILE"
exit 1
@@ -59,7 +59,7 @@ echo "[run_uav] MAVLink connection: $CONN"
# Run via aerpawlib
echo "[run_uav] Starting UAV runner..."
python3 -u -m aerpawlib \
python3 -m aerpawlib \
--script client.uav_runner \
--conn "$CONN" \
--vehicle drone
-100
View File
@@ -1,100 +0,0 @@
#!/bin/bash
# Derive number of UAVs from scenario.csv
NUM_UAVS=$(python3 -c "
import csv, os
csv_path = '/root/miSim/aerpaw/config/scenario.csv'
with open(csv_path, 'r') as f:
reader = csv.reader(f, skipinitialspace=True)
header = [h.strip() for h in next(reader)]
row = next(reader)
col = header.index('initialPositions')
vals = [v.strip() for v in row[col].strip().split(',') if v.strip()]
print(len(vals) // 3)
" 2>/dev/null || echo 0)
cd $PROFILE_DIR"/ProfileScripts/Radio/Helpers"
if [ "$NUM_UAVS" -eq 2 ]; then
# Direct 1-to-1 mode: UAV 0 = TX only, UAV 1 = RX only
echo "[Radio] 2-UAV direct mode: UAV_ID=$UAV_ID"
if [ "$UAV_ID" -eq 0 ]; then
# TX only (--num-uavs 1 disables TDM muting)
screen -S txGRC -dm \
bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh --num-uavs 1 \
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
else
# RX only (--num-uavs 1 disables TDM tagging)
screen -S rxGRC -dm \
bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh --num-uavs 1 \
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
screen -S power -dm \
bash -c "stdbuf -oL -eL tail -F /root/Power\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
screen -S quality -dm \
bash -c "stdbuf -oL -eL tail -F /root/Quality\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
screen -S snr -dm \
bash -c "stdbuf -oL -eL tail -F /root/SNR\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
screen -S noisefloor -dm \
bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
screen -S freqoffset -dm \
bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
fi
else
# 3+ UAVs: full TDM mode — every node runs both TX and RX
echo "[Radio] TDM mode: $NUM_UAVS UAVs, UAV_ID=$UAV_ID"
screen -S rxGRC -dm \
bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh \
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
screen -S power -dm \
bash -c "stdbuf -oL -eL tail -F /root/Power\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
screen -S quality -dm \
bash -c "stdbuf -oL -eL tail -F /root/Quality\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
screen -S snr -dm \
bash -c "stdbuf -oL -eL tail -F /root/SNR\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
screen -S noisefloor -dm \
bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
screen -S freqoffset -dm \
bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
screen -S txGRC -dm \
bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh \
2>&1 | ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
fi
cd -
-30
View File
@@ -1,30 +0,0 @@
#!/bin/bash
### Sample GPS logger portion
# use vehicle type generic to skip the arming requirement
export VEHICLE_TYPE="${VEHICLE_TYPE:-generic}"
# GPS Logger sample application (this does not move the vehicle)
#cd $PROFILE_DIR"/ProfileScripts/Vehicle/Helpers"
#
#screen -S vehicle -dm \
# bash -c "stdbuf -oL -eL ./gpsLoggerHelper.sh \
# 2> >(ts $TS_FORMAT >> $RESULTS_DIR/${LOG_PREFIX}_vehicle_log_err.txt) \
# | ts $TS_FORMAT \
# | tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"
#
#cd -
### Actual control portion (custom)
export VEHICLE_TYPE="${VEHICLE_TYPE:-drone}" # out of rover, drone, generic
cd /root/miSim/aerpaw
# Use screen/ts/tee aerpawism from sample script
screen -S vehicle -dm \
bash -c "stdbuf -oL -eL ./run_uav.sh testbed \
| ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"
cd -
-11
View File
@@ -1,11 +0,0 @@
#!/bin/bash
cd /root/miSim/aerpaw
# Compile controller
/bin/bash compile.sh
# Run controller
./build/controller_app
cd -
-50
View File
@@ -1,50 +0,0 @@
#!/bin/bash
/root/stopexperiment.sh
source /root/.ap-set-experiment-env.sh
source /root/.bashrc
# set path to client config YAML
export AERPAW_CLIENT_CONFIG=/root/miSim/aerpaw/config/client1.yaml
export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
export PYTHONPATH=/usr/local/lib/python3/dist-packages/
export EXP_NUMBER=${EXP_NUMBER:-1}
if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
export VEHICLE_TYPE=drone
elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
export VEHICLE_TYPE=rover
else
export VEHICLE_TYPE=none
fi
if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
export LAUNCH_MODE=EMULATION
elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
export LAUNCH_MODE=TESTBED
else
export LAUNCH_MODE=none
fi
# prepare results directory
export UAV_ID=$(python3 -c "import yaml; print(yaml.safe_load(open('$AERPAW_CLIENT_CONFIG'))['uav_id'])")
export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
export RESULTS_DIR="/root/Results/uav${UAV_ID}_${RESULTS_DIR_TIMESTAMP}"
mkdir -p "$RESULTS_DIR"
export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
export TX_FREQ=3.32e9
export RX_FREQ=3.32e9
export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
cd $PROFILE_DIR"/ProfileScripts"
./Radio/startRadio.sh
#./Traffic/startTraffic.sh
./Vehicle/startVehicle.sh
schedule_stop.sh 30
@@ -1,47 +0,0 @@
#!/bin/bash
/root/stopexperiment.sh
source /root/.ap-set-experiment-env.sh
source /root/.bashrc
export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
export PYTHONPATH=/usr/local/lib/python3/dist-packages/
export EXP_NUMBER=${EXP_NUMBER:-1}
if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
export VEHICLE_TYPE=drone
elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
export VEHICLE_TYPE=rover
else
export VEHICLE_TYPE=none
fi
if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
export LAUNCH_MODE=EMULATION
elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
export LAUNCH_MODE=TESTBED
else
export LAUNCH_MODE=none
fi
# prepare results directory
export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
export RESULTS_DIR="/root/Results/controller_${RESULTS_DIR_TIMESTAMP}"
mkdir -p "$RESULTS_DIR"
export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
export TX_FREQ=3.32e9
export RX_FREQ=3.32e9
export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
cd $PROFILE_DIR"/ProfileScripts"
screen -S controller -dm \
bash -c "stdbuf -oL -eL ./Vehicle/startVehicle.sh \
| ts $TS_FORMAT \
| tee $RESULTS_DIR/$LOG_PREFIX\_controller_log.txt"
schedule_stop.sh 30
+3 -5
View File
@@ -6,11 +6,9 @@ classdef cone
label = "";
% Spatial
center = NaN;
radius = NaN;
height = NaN;
tilt = 0; % degrees, 0=nadir 90=horizon
azimuth = 0; % degrees, 0=+Y 90=+X clockwise
center = NaN;
radius = NaN;
height = NaN;
% Plotting
surface;
+12 -16
View File
@@ -1,23 +1,19 @@
function obj = initialize(obj, center, radius, height, tag, label, tilt, azimuth)
function obj = initialize(obj, center, radius, height, tag, label)
arguments (Input)
obj (1, 1) {mustBeA(obj, "cone")};
center (1, 3) double;
radius (1, 1) double;
height (1, 1) double;
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
label (1, 1) string = "";
tilt (1, 1) double = 0;
azimuth (1, 1) double = 0;
obj (1, 1) {mustBeA(obj, "cone")};
center (1, 3) double;
radius (1, 1) double;
height (1, 1) double;
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
label (1, 1) string = "";
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "cone")};
end
obj.center = center;
obj.radius = radius;
obj.height = height;
obj.tag = tag;
obj.label = label;
obj.tilt = tilt;
obj.azimuth = azimuth;
obj.center = center;
obj.radius = radius;
obj.height = height;
obj.tag = tag;
obj.label = label;
end
-11
View File
@@ -21,17 +21,6 @@ function [obj, f] = plot(obj, ind, f, maxAlt)
% Scale to match height
Z = Z * maxAlt;
% Rotate mesh around apex to match boresight tilt and azimuth.
% Apex sits at [0, 0, maxAlt] before center translation.
% Convention: tilt 0=nadir, 90=horizon; azimuth 0=+Y, 90=+X, clockwise.
Ry = [cosd(obj.tilt), 0, -sind(obj.tilt); 0, 1, 0; sind(obj.tilt), 0, cosd(obj.tilt)];
Rz = [sind(obj.azimuth), -cosd(obj.azimuth), 0; cosd(obj.azimuth), sind(obj.azimuth), 0; 0, 0, 1];
R = Rz * Ry;
pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
X = reshape(pts(1, :), size(X));
Y = reshape(pts(2, :), size(Y));
Z = reshape(pts(3, :) + maxAlt, size(Z));
% Move to center location
X = X + obj.center(1);
Y = Y + obj.center(2);
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="okabeIto.m" type="File"/>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="exportThesisFig.m" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="aerpaw/scripts" Type="Relative"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="6402cbb5-c767-4c8b-bd7c-b2d7cf1055fc" type="Reference"/>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="test"/>
</Category>
</Info>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test_rfSensor.m" type="File"/>
@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="clearRssCache.m" type="File"/>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="rfSensor.m" type="File"/>
@@ -1,6 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
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