47 Commits

Author SHA1 Message Date
bdc31ccad5 plot script fixes 2026-03-04 23:06:06 -08:00
d5c7f4f11f finalized plotting utility 2026-03-04 22:32:39 -08:00
110ff87c57 type error fix 2026-03-04 21:27:51 -08:00
51e7533369 added radio plotting tools 2026-03-04 21:22:33 -08:00
3fd4462f11 plotting update 2026-03-04 18:42:17 -08:00
12b6e79f1e fixed GPS log out path 2026-03-04 18:21:39 -08:00
e801018d9c radio experiment TDM working 2026-03-04 17:26:50 -08:00
d5307f63e9 seems to line up well again, constrainMotion updates 2026-03-03 20:14:55 -08:00
ac52e0414d scenario update, quadprog issue 2026-03-03 19:32:13 -08:00
f140b55a63 obstacle respected now 2026-03-03 18:53:19 -08:00
6b5d33962b obstacles in but ignored 2026-03-03 16:42:15 -08:00
8ebeda3bf0 scenario - obstacle - one around, one over 2026-03-03 16:22:13 -08:00
fe7b1b2ed3 per-UAV parameters 2026-03-03 16:18:07 -08:00
252423eb29 moved reader out of miSim, went to event-based guidance 2026-03-03 15:53:22 -08:00
351a9bd16f removed prompt to continue 2026-03-03 15:22:10 -08:00
2b853466f2 results compare favorably 2026-03-02 19:06:45 -08:00
d49bf61d1d scenario edits 2026-03-02 18:18:40 -08:00
032f50774f improved globe plotting 2026-03-02 16:15:03 -08:00
e40d2e4614 moved origin to get more space from geofence 2026-03-02 12:15:01 -08:00
387d6aea56 scenario csv on both platforms 2026-02-28 19:36:58 -08:00
0bf293c95e added slack in collision avoidance constraint 2026-02-27 16:06:10 -08:00
db6df5f263 csv parse update 2026-02-25 11:44:59 -08:00
d89fa38ba1 testing fixes 2026-02-25 11:02:56 -08:00
c2fa2b524a added constraint violation recovery mechanism 2026-02-24 19:30:14 -08:00
bb97502be5 codegen fixes, bug fixes, gets running on testbed environment 2026-02-24 19:05:54 -08:00
fb9feac23d gps log plotting 2026-02-16 11:19:10 -08:00
fd6ebf538c aerpaw gps csv reader 2026-02-15 21:50:13 -08:00
a328eae126 gps logging updates 2026-02-15 17:29:14 -08:00
c060dfad06 respect geofence, move from socket to async/await 2026-02-13 18:55:07 -08:00
05bf99f061 more config cleanup 2026-02-13 18:16:27 -08:00
77ac58a8a2 config cleanup 2026-02-13 18:06:06 -08:00
525d213e6a project cleanup 2026-02-07 14:36:53 -08:00
f434e1a685 logging consistency 2026-02-02 12:16:13 -08:00
330c1e5d54 message type updates 2026-02-01 16:02:18 -08:00
f6e1f13bb5 removed potentially faulty environment detection in favor of explicit setting 2026-02-01 11:34:35 -08:00
79b03345ba refactor experiment config 2026-02-01 11:08:04 -08:00
a965dff4ca added parallel message receiving for previously implemented messaging where necessary 2026-01-30 18:28:19 -08:00
448db1e0e3 added RTL and LAND capabilities 2026-01-30 18:16:33 -08:00
dd82cb3956 kinda working 2026-01-30 15:56:00 -08:00
6b8e26eb69 added real autopilot connection info 2026-01-29 22:07:53 -08:00
654de7c2a1 allowed connection to real autopilot 2026-01-29 21:11:45 -08:00
338bb6c340 added aerpawlib capabilities to uav script 2026-01-29 20:56:54 -08:00
6604928f8f reorganized and added aerpawlib submodule 2026-01-29 20:08:51 -08:00
aed1924297 sending starting positions to agents (not verified on AERPAW yet) 2026-01-29 16:42:19 -08:00
fe106f31cd cleanup demo 2026-01-28 23:20:11 -08:00
8c5c315380 basic implementation of client/server for AERPAW, whole lot of mess included 2026-01-28 22:29:17 -08:00
b444e44d33 experiment setup 2026-01-28 15:47:09 -08:00
55 changed files with 142 additions and 627 deletions

1
.gitignore vendored
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@@ -48,7 +48,6 @@ sandbox/*
# Figures
*.fig
*.png
# Python Virtual Environment
aerpaw/venv/

3
.gitmodules vendored
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@@ -0,0 +1,3 @@
[submodule "aerpaw/aerpawlib"]
path = aerpaw/aerpawlib
url = https://github.com/morzack/aerpawlib-vehicle-control.git

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@@ -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;

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@@ -15,9 +15,6 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
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;
@@ -36,4 +33,4 @@ 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.alphaTilt) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label));
end
end

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@@ -1,4 +1,4 @@
function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useDoubleIntegrator, dampingCoeff, dt)
function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
arguments (Input)
obj (1, 1) {mustBeA(obj, "agent")};
domain (1, 1) {mustBeGeometry};
@@ -6,21 +6,11 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
timestepIndex (1, 1) double;
index (1, 1) double;
agents (:, 1) {mustBeA(agents, "cell")};
useDoubleIntegrator (1, 1) logical = false;
dampingCoeff (1, 1) double = 2.0;
dt (1, 1) double = 1.0;
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(:))
@@ -85,25 +75,20 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
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 gradNorm < 1e-100
a_gradient = zeros(1, 3);
else
% Scale so steady-state step targetRate (matching SI behavior)
a_gradient = (targetRate * dampingCoeff / (gradNorm * dt)) * gradC;
end
% Semi-implicit Euler: unconditionally stable for any dampingCoeff and dt
obj.vel = (obj.vel + a_gradient * 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 gradNorm >= 1e-100
obj.pos = obj.pos + (targetRate / gradNorm) * gradC;
end
pNext = obj.pos + (targetRate / gradNorm) * gradC;
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;
if isa(obj.collisionGeometry, "rectangularPrism")

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@@ -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
@@ -60,20 +60,16 @@ function [obj] = constrainMotion(obj)
end
end
idx = length(h(triu(true(size(h)), 1)));
obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
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;
@@ -84,52 +80,46 @@ function [obj] = constrainMotion(obj)
end
end
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
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;
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
idx = idx + 6;
end
if coder.target('MATLAB')
@@ -143,41 +133,21 @@ function [obj] = constrainMotion(obj)
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;
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 * 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));
% 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
b(kk) = obj.barrierGain * max(0, hComms(ii, jj))^obj.barrierExponent;
kk = kk + 1;
end
end
end
obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
% 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')
@@ -187,8 +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
@@ -197,9 +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
@@ -207,16 +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

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@@ -1,4 +1,4 @@
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology)
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};
@@ -11,9 +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;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, "miSim")};
@@ -89,18 +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;
% Compute adjacency matrix and network topology
% Compute adjacency matrix and lesser neighbors
obj = obj.updateAdjacency();
if obj.useFixedTopology
obj.constraintAdjacencyMatrix = obj.adjacency;
else
obj = obj.lesserNeighbor();
end
obj = obj.lesserNeighbor();
% Set up times to iterate over
obj.times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
@@ -116,34 +104,11 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
% 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)
nLNAPairs = sum(triu(obj.constraintAdjacencyMatrix, 1), "all");
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();

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@@ -79,23 +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
% ---- Build domain --------------------------------------------------------
dom = rectangularPrism;
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
@@ -141,7 +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);
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
end

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
@@ -17,17 +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
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)
@@ -45,7 +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
@@ -67,6 +61,7 @@ classdef miSim
obj (1, 1) miSim
end
obj.domain = rectangularPrism;
obj.objective = sensingObjective;
obj.obstacles = {rectangularPrism};
obj.agents = {agent};
end

View File

@@ -30,19 +30,12 @@ function [obj] = run(obj)
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
% Determine desired communications links
if ~obj.useFixedTopology
obj = obj.lesserNeighbor();
end
% Log constraint adjacency for this timestep
if coder.target('MATLAB')
obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
end
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.agents, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep);
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
@@ -50,9 +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))];
@@ -71,12 +63,10 @@ function [obj] = run(obj)
end
end
% Close video
if coder.target('MATLAB')
if obj.makeVideo
% Close video file
v.close();
end
end
end

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

View File

@@ -7,11 +7,11 @@ function validate(obj)
%% Communications Network Validators
if max(conncomp(graph(obj.adjacency))) ~= 1
error("Network 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
@@ -21,8 +21,9 @@ function validate(obj)
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
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
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

View File

@@ -14,21 +14,17 @@ function writeInits(obj)
comRanges = cellfun(@(x) x.commsGeometry.radius, 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, obj.obstacles, 'UniformOutput', false));
obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, obj.obstacles, 'UniformOutput', false));
% Combine with simulation parameters
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", size(obj.obstacles, 1), ...
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ...
"alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
"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, ...
"obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
"objectiveIntegral", sum(obj.domain.objective.values(:)));
"pos", pos);
% Save all parameters to output file
initsFile = strcat(obj.artifactName, "_miSimInits");

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")};
@@ -38,14 +36,9 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
obj.values = obj.values ./ max(obj.values, [], "all");
% 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;
idx = obj.values == 1;
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

View File

@@ -11,7 +11,7 @@ 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

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 = [];

1
aerpaw/aerpawlib Submodule

Submodule aerpaw/aerpawlib added at 705fc699ef

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:
@@ -32,7 +32,7 @@ environments:
mavlink:
ip: "192.168.32.26"
port: 14550
# Controller runs on host machine (192.168.109.1 from E-VM perspective)
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
controller:
ip: "192.168.109.1"
ip: "192.168.122.1"
port: 5000

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:
@@ -32,7 +32,7 @@ environments:
mavlink:
ip: "192.168.32.26"
port: 14550
# Controller runs on host machine (192.168.109.1 from E-VM perspective)
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
controller:
ip: "192.168.109.1"
ip: "192.168.122.1"
port: 5000

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
1, 150, 30.0, 0.1, 2.0, 1, 1, 1, "5.0, 5.0", "25.0, 25.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "80.0, 80.0, 80.0", "55.0, 55.0", "40, 25, 25, 40", 0.15, "15.0, 10.0, 40.0, 5.0, 10.0, 45.0", 1, "1.0, 25.0, 0.0", "30.0, 30.0, 50.0", 1, 2.0, 1
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax
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
2 1 5 150 120 30.0 0.1 2.0 1.0 1 2.0 1 100 1 3 5.0, 5.0 3.0, 3.0 25.0, 25.0 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 80.0, 80.0, 80.0 50.0, 50.0, 80.0 55.0, 55.0 35.0, 35.0 40, 25, 25, 40 10, 5, 5, 10 0.15 15.0, 10.0, 40.0, 5.0, 10.0, 45.0 5.0, 10.0, 45.0, 15.0, 10.0, 35.0 1 1.0, 25.0, 0.0 2.0, 15.0, 0.0 30.0, 30.0, 50.0 25.0, 25.0, 50.0 1 2.0 1

View File

@@ -133,11 +133,6 @@
<Size type="coderapp.internal.codertype.Dimension"/>
<Size type="coderapp.internal.codertype.Dimension"/>
</Types>
<Types id="27" type="coderapp.internal.codertype.PrimitiveType">
<ClassName>int32</ClassName>
<Size type="coderapp.internal.codertype.Dimension"/>
<Size type="coderapp.internal.codertype.Dimension"/>
</Types>
</Types>
</coderapp.internal.interface.project.Interface>
</MF0>
@@ -1099,7 +1094,7 @@
</Artifacts>
<BuildFolder type="coderapp.internal.util.mfz.FileSpec"/>
<Success>true</Success>
<Timestamp>2026-03-11T17:11:03</Timestamp>
<Timestamp>2026-03-03T19:58:03</Timestamp>
</MainBuildResult>
</coderapp.internal.mlc.mfz.MatlabCoderProjectState>
</MF0>

View File

@@ -1,17 +1,12 @@
#include <iostream>
#include "controller.h"
#include "controller.h"
#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);

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

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

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

View File

@@ -1,15 +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"
cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.

View File

@@ -24,25 +24,16 @@ function [f, R] = plotRadioLogs(resultsPath)
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)"];
metricNames = ["SNR", "Power", "Quality"];
yLabels = ["SNR (dB)", "Power (dB)", "Quality"];
f = figure;
tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
tl = tiledlayout(3, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
for mi = 1:numel(metricNames)
ax = nexttile(tl);

View File

@@ -4,19 +4,19 @@ function R = readRadioLogs(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);
@@ -43,15 +43,13 @@ function R = readRadioLogs(logPath)
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>

View File

@@ -1,5 +1,5 @@
%% Plot AERPAW logs (trajectory, radio)
resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % Define path to results copied from AERPAW platform
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

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

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 -

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 -

View File

@@ -1,11 +0,0 @@
#!/bin/bash
cd /root/miSim/aerpaw
# Compile controller
/bin/bash compile.sh
# Run controller
./build/controller_app
cd -

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

View File

@@ -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

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="aerpaw/scripts" Type="Relative"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="6402cbb5-c767-4c8b-bd7c-b2d7cf1055fc" type="Reference"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="scripts" type="File"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="startexperiment_controller.sh" type="File"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="startRadio.sh" type="File"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="startexperiment.sh" type="File"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="startVehicle.sh" type="File"/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>

View File

@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="startVehicle_controller.sh" type="File"/>

View File

@@ -1,2 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
<Info location="t1.zip" type="File"/>

BIN
t1.zip Normal file

Binary file not shown.

View File

@@ -57,16 +57,13 @@ classdef parametricTestSuite < matlab.unittest.TestCase
end
% Set up simulation
tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, tc.makePlots, tc.makeVideo, logical(params.useDoubleIntegrator), params.dampingCoeff, logical(params.useFixedTopology));
tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, tc.makePlots, tc.makeVideo);
% Save simulation parameters to output file
tc.testClass.writeInits();
% Run
tc.testClass = tc.testClass.run();
% Save results and clean up
tc.testClass = tc.testClass.teardown();
end
function csv_parametric_tests_random_agents(tc)
% Read in parameters to iterate over
@@ -150,7 +147,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
end
% randomly shuffle agents to make the network more interesting (probably)
agents = agents(randperm(numel(agents)));
agents = agents(randperm(numel(agents)));
% Set up obstacles
obstacles = cell(params.numObstacles(ii), 1);

View File

@@ -33,8 +33,6 @@ classdef test_miSim < matlab.unittest.TestCase
initialStepSize = 0.2; % gradient ascent step size at the first iteration. Decreases linearly to 0 based on maxIter.
minAgents = 3; % Minimum number of agents to be randomly generated
maxAgents = 4; % Maximum number of agents to be randomly generated
useDoubleIntegrator = false;
dampingCoeff = 2;
agents = cell(0, 1);
% Collision
@@ -54,7 +52,6 @@ classdef test_miSim < matlab.unittest.TestCase
sensor = sigmoidSensor;
% Communications
useFixedTopology = false;
minCommsRange = 3; % Minimum randomly generated collision geometry size
maxCommsRange = 5; % Maximum randomly generated collision geometry size
commsRanges = NaN;
@@ -227,7 +224,7 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
end
function miSim_run(tc)
% randomly create obstacles
@@ -366,7 +363,7 @@ classdef test_miSim < matlab.unittest.TestCase
end
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Write out initialization state
tc.testClass.writeInits();
@@ -400,7 +397,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.obstacles = cell(0, 1);
tc.makePlots = false;
tc.makeVideo = false;
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
centerIdx = floor(size(tc.testClass.partitioning, 1) / 2);
tc.verifyEqual(tc.testClass.partitioning(centerIdx, centerIdx:(centerIdx + 2)), [2, 3, 1]); % all three near center
@@ -425,7 +422,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.obstacles = cell(0, 1);
tc.makePlots = false;
tc.makeVideo = false;
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
close(tc.testClass.fPerf);
tc.verifyEqual(unique(tc.testClass.partitioning), [0; 1]);
@@ -453,7 +450,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize the simulation
tc.obstacles = cell(0, 1);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Run the simulation
tc.testClass = tc.testClass.run();end
@@ -488,7 +485,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize the simulation
tc.obstacles = cell(0, 1);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Run the simulation
tc.testClass.run();
@@ -534,7 +531,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, tc.collisionRanges(2) *1.1 + yOffset, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Run the simulation
tc.testClass.run();
@@ -574,7 +571,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Run the simulation
tc.testClass = tc.testClass.run();
@@ -617,7 +614,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.minAlt = 0;
tc.makePlots = false;
tc.makeVideo = false;
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Communications link should be established
tc.assertEqual(tc.testClass.adjacency, logical(true(2)));
@@ -662,7 +659,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.minAlt = 0;
tc.makePlots = false;
tc.makeVideo = false;
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
@@ -716,7 +713,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.minAlt = 0;
tc.makePlots = false;
tc.makeVideo = false;
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo);
% Constraint adjacency matrix defined by LNA should be as follows
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...

View File

@@ -4,12 +4,12 @@ function f = objectiveFunctionWrapper(center, sigma)
% composite objectives in particular
arguments (Input)
center (:, 2) double;
sigma (:, 2, 2) double = eye(2);
sigma (2, 2) double = eye(2);
end
arguments (Output)
f (1, 1) {mustBeA(f, "function_handle")};
end
assert(size(center, 1) == size(sigma, 1));
f = @(x,y) sum(cell2mat(arrayfun(@(i) mvnpdf([x(:), y(:)], center(i,:), squeeze(sigma(i, :, :))), 1:size(center,1), "UniformOutput", false)), 2);
f = @(x,y) sum(cell2mat(arrayfun(@(i) mvnpdf([x(:), y(:)], center(i,:), sigma), 1:size(center,1), "UniformOutput", false)), 2);
end