24 Commits

Author SHA1 Message Date
kdee a30dfe6be7 ran 3 new experiments on AERPAW simulation to test before submitting 2026-05-25 14:07:49 -07:00
kdee 9c65bf7880 fixed multi-objective support, collected sim data on 3 new experiments 2026-05-24 20:28:12 -07:00
kdee fbcaa32abd first experiment tweaks 2026-04-08 09:41:30 -07:00
kdee 09a10abfd5 controller logging and analysis improvements 2026-04-08 00:02:54 -07:00
kdee 87060ca123 analysis script fixes 2026-04-06 21:34:48 -07:00
kdee f7902ee220 space out flyouts further 2026-04-06 20:30:55 -07:00
kdee 5c90219322 aerpaw collision distance log monitoring 2026-04-06 19:34:15 -07:00
kdee d3bdc80e64 scaled up scenario for better collision safety 2026-04-06 18:44:17 -07:00
kdee f3f9ec3db2 added minimum command spacing log parser and check 2026-04-06 18:16:00 -07:00
kdee 9564a5707f AERPAW bug fixes for first experiment 2026-04-05 14:54:56 -07:00
kdee 789aecc560 experiment 1 obstacle collision fixes completed 2026-04-05 14:24:10 -07:00
kdee bd452b7180 fixed data logging codegen logic 2026-04-05 13:41:43 -07:00
kdee 31e88a8535 first aerpaw test prepared 2026-04-02 13:19:14 -07:00
kdee f598a832fa big steppa 2026-04-02 10:04:51 -07:00
kdee ac09a59c00 more graceful method of moving UAVs to initial states in AERPAW without collision 2026-04-01 22:02:38 -07:00
kdee 7a3fcbd4dc two_around_wall experiment refinement 2026-04-01 21:27:32 -07:00
kdee 8db6c70f46 better scenario final altitude parity 2026-04-01 17:55:30 -07:00
kdee 43229a3a09 project files 2026-04-01 17:48:41 -07:00
kdee 3b3cab2089 added full plotting from logged outputs 2026-04-01 09:48:06 -07:00
kdee b7bb2dec53 added function to initialize sim from saved-off inits file 2026-04-01 09:11:40 -07:00
kdee 60475162e4 no more rectangular collision geoms 2026-03-31 22:19:53 -07:00
kdee 8da65278a2 refactored constraint plotting to remove superfluous property 2026-03-31 22:10:43 -07:00
kdee 0bcdd73882 interface updates for test cases 2026-03-31 21:49:06 -07:00
kdee c3fa1de914 included features from SPAWC 2026 branch 2026-03-31 21:18:02 -07:00
80 changed files with 1016 additions and 325 deletions
+2
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@@ -4,6 +4,7 @@
*.autosave *.autosave
*.slx.r* *.slx.r*
*.mdl.r* *.mdl.r*
*.bak
# Derived content-obscured files # Derived content-obscured files
*.p *.p
@@ -48,6 +49,7 @@ sandbox/*
# Figures # Figures
*.fig *.fig
*.png
# Python Virtual Environment # Python Virtual Environment
aerpaw/venv/ aerpaw/venv/
+2 -1
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@@ -15,6 +15,7 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
end end
obj.pos = pos; obj.pos = pos;
obj.lastPos = pos;
obj.vel = zeros(1, 3); obj.vel = zeros(1, 3);
obj.lastVel = zeros(1, 3); obj.lastVel = zeros(1, 3);
obj.collisionGeometry = collisionGeometry; obj.collisionGeometry = collisionGeometry;
@@ -35,4 +36,4 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
% Initialize FOV cone % Initialize FOV cone
obj.fovGeometry = 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)); 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
+7 -2
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@@ -14,6 +14,13 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
obj (1, 1) {mustBeA(obj, "agent")}; obj (1, 1) {mustBeA(obj, "agent")};
end 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 % Collect objective function values across partition
partitionMask = partitioning == index; partitionMask = partitioning == index;
if ~any(partitionMask(:)) if ~any(partitionMask(:))
@@ -79,10 +86,8 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
gradNorm = norm(gradC); gradNorm = norm(gradC);
% Compute unconstrained next state % Compute unconstrained next state
obj.lastPos = obj.pos;
if useDoubleIntegrator if useDoubleIntegrator
% Double-integrator: gradient produces desired acceleration with damping % Double-integrator: gradient produces desired acceleration with damping
obj.lastVel = obj.vel;
if gradNorm < 1e-100 if gradNorm < 1e-100
a_gradient = zeros(1, 3); a_gradient = zeros(1, 3);
else else
+29 -25
View File
@@ -39,10 +39,10 @@ function [obj] = constrainMotion(obj)
h(logical(eye(nAgents))) = 0; % self value is 0 h(logical(eye(nAgents))) = 0; % self value is 0
for ii = 1:(nAgents - 1) for ii = 1:(nAgents - 1)
for jj = (ii + 1):nAgents for jj = (ii + 1):nAgents
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(ii, jj) = norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
h(jj, ii) = h(ii, jj); h(jj, ii) = h(ii, jj);
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - obj.agents{jj}.pos); 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 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
% Slack derived from existing params: recovery velocity = max gradient approach velocity. % Slack derived from existing params: recovery velocity = max gradient approach velocity.
% Correction splits between 2 agents, so |A| = 2*r_sum % Correction splits between 2 agents, so |A| = 2*r_sum
@@ -60,8 +60,10 @@ function [obj] = constrainMotion(obj)
end end
end end
idx = length(h(triu(true(size(h)), 1))); idx = length(h(triu(true(size(h)), 1)));
obj.barriers(1:idx, obj.timestepIndex) = 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; idx = idx + 1;
hObs = NaN(nAgents, size(obj.obstacles, 1)); hObs = NaN(nAgents, size(obj.obstacles, 1));
@@ -69,11 +71,11 @@ function [obj] = constrainMotion(obj)
for ii = 1:nAgents for ii = 1:nAgents
for jj = 1:size(obj.obstacles, 1) for jj = 1:size(obj.obstacles, 1)
% find closest position to agent on/in obstacle % find closest position to agent on/in obstacle
cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.pos); cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.lastPos);
hObs(ii, jj) = dot(obj.agents{ii}.pos - cPos, obj.agents{ii}.pos - cPos) - obj.agents{ii}.collisionGeometry.radius^2; hObs(ii, jj) = dot(obj.agents{ii}.lastPos - cPos, obj.agents{ii}.lastPos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - cPos); A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - cPos);
% Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i % Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i
r_i = obj.agents{ii}.collisionGeometry.radius; r_i = obj.agents{ii}.collisionGeometry.radius;
v_max_i = obj.agents{ii}.initialStepSize / obj.timestep; v_max_i = obj.agents{ii}.initialStepSize / obj.timestep;
@@ -84,7 +86,9 @@ function [obj] = constrainMotion(obj)
end end
end end
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1); if coder.target('MATLAB')
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
end
idx = idx + numel(hObs); idx = idx + numel(hObs);
% Set up domain constraints (walls and ceiling only) % Set up domain constraints (walls and ceiling only)
@@ -93,48 +97,45 @@ function [obj] = constrainMotion(obj)
h_xMin = 0.0; h_xMax = 0.0; h_yMin = 0.0; h_yMax = 0.0; h_zMin = 0.0; h_zMax = 0.0; 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 for ii = 1:nAgents
% X minimum % X minimum
h_xMin = (obj.agents{ii}.pos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius; h_xMin = (obj.agents{ii}.lastPos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0]; A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
% X maximum % X maximum
h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.pos(1)) - obj.agents{ii}.collisionGeometry.radius; h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.lastPos(1)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0]; A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
% Y minimum % Y minimum
h_yMin = (obj.agents{ii}.pos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius; h_yMin = (obj.agents{ii}.lastPos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0]; A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
% Y maximum % Y maximum
h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.pos(2)) - obj.agents{ii}.collisionGeometry.radius; h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.lastPos(2)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0]; A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
b(kk) = obj.barrierGain * max(0, h_yMax)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_yMax)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
% Z minimum enforce z >= minAlt + radius (not just z >= domain floor + radius) % Z minimum enforce z >= minAlt + radius (not just z >= domain floor + radius)
h_zMin = (obj.agents{ii}.pos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius; h_zMin = (obj.agents{ii}.lastPos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1]; A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
% Z maximum % Z maximum
h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.pos(3)) - obj.agents{ii}.collisionGeometry.radius; h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.lastPos(3)) - obj.agents{ii}.collisionGeometry.radius;
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1]; A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent; b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
kk = kk + 1; kk = kk + 1;
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax]; if coder.target('MATLAB')
idx = idx + 6; obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
end 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 end
% Add communication network constraints % Add communication network constraints
@@ -145,9 +146,9 @@ function [obj] = constrainMotion(obj)
if obj.constraintAdjacencyMatrix(ii, jj) if obj.constraintAdjacencyMatrix(ii, jj)
paddingFactor = 0.9; % Barrier at 90% of actual range; real comms still work beyond this 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]); r_comms = paddingFactor * min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius]);
hComms(ii, jj) = r_comms^2 - norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2; hComms(ii, jj) = r_comms^2 - norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2;
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (obj.agents{ii}.pos - obj.agents{jj}.pos); 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 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
% One-step forward invariance: b = h/dt ensures h cannot % One-step forward invariance: b = h/dt ensures h cannot
@@ -164,7 +165,10 @@ function [obj] = constrainMotion(obj)
end end
end end
end end
obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
if coder.target('MATLAB')
obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
end
% Double-integrator: transform QP from velocity to acceleration space. % Double-integrator: transform QP from velocity to acceleration space.
% Single-integrator constraint: A * v <= b % Single-integrator constraint: A * v <= b
@@ -224,4 +228,4 @@ function [obj] = constrainMotion(obj)
% Running at the simulation level is just meant to simplify the % Running at the simulation level is just meant to simplify the
% simulation % simulation
end end
+6 -2
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@@ -109,8 +109,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
% Prepare performance data store (at t = 0, all have 0 performance) % 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)]; 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 end
% Create initial partitioning % Create initial partitioning
@@ -138,6 +136,12 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
% Initialize variable that will store barrier function values per timestep for analysis purposes % Initialize variable that will store barrier function values per timestep for analysis purposes
obj.barriers = NaN(obj.numBarriers, size(obj.times, 1)); 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 % Set up plots showing initialized state
obj = obj.plot(); obj = obj.plot();
+87
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@@ -0,0 +1,87 @@
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));
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
% ---- 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);
end
+4 -4
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@@ -7,7 +7,6 @@ classdef miSim
timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays) timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
maxIter = NaN; % maximum number of simulation iterations maxIter = NaN; % maximum number of simulation iterations
domain; domain;
objective;
obstacles; % geometries that define obstacles within the domain obstacles; % geometries that define obstacles within the domain
agents; % agents that move within the domain agents; % agents that move within the domain
adjacency = false(0, 0); % Adjacency matrix representing communications network graph adjacency = false(0, 0); % Adjacency matrix representing communications network graph
@@ -28,6 +27,7 @@ classdef miSim
spatialPlotIndices = [6, 4, 3, 2]; spatialPlotIndices = [6, 4, 3, 2];
numBarriers = 0; % Number of barrier functions needed numBarriers = 0; % Number of barrier functions needed
barriers = []; % log barrier function values at each timestep for analysis barriers = []; % log barrier function values at each timestep for analysis
constraintAdjacencyHist = []; % log constraint adjacency matrix at each timestep
end end
properties (Access = private) properties (Access = private)
@@ -54,7 +54,6 @@ classdef miSim
partitionGraphIndex = 1; partitionGraphIndex = 1;
% CBF plotting % CBF plotting
h; % h function values
hf; % h function plotting figure hf; % h function plotting figure
caPlot; % objects for collision avoidance h function plot caPlot; % objects for collision avoidance h function plot
obsPlot; % objects for obstacle h function plot obsPlot; % objects for obstacle h function plot
@@ -67,12 +66,13 @@ classdef miSim
obj (1, 1) miSim obj (1, 1) miSim
end end
obj.domain = rectangularPrism; obj.domain = rectangularPrism;
obj.objective = sensingObjective;
obj.obstacles = {rectangularPrism}; obj.obstacles = {rectangularPrism};
obj.agents = {agent}; obj.agents = {agent};
end end
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo); [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology);
[obj] = initializeFromCsv(obj, csvPath); [obj] = initializeFromCsv(obj, csvPath);
[obj] = initializeFromInits(obj, initsPath);
[obj] = plotFromSimHist(obj, initsPath, histPath);
[obj] = run(obj); [obj] = run(obj);
[obj] = lesserNeighbor(obj); [obj] = lesserNeighbor(obj);
[obj] = constrainMotion(obj); [obj] = constrainMotion(obj);
+93
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@@ -0,0 +1,93 @@
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
+13 -4
View File
@@ -6,6 +6,10 @@ function obj = plotH(obj)
obj (1, 1) {mustBeA(obj, "miSim")}; obj (1, 1) {mustBeA(obj, "miSim")};
end 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; obj.hf = figure;
tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact"); tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
@@ -15,7 +19,7 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)"); xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Collision Avoidance"); title(obj.hf.Children(1).Children(1), "Collision Avoidance");
hold(obj.hf.Children(1).Children(1), "on"); hold(obj.hf.Children(1).Children(1), "on");
obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)'); obj.caPlot = plot(obj.barriers(1:nCA, :)');
legendStrings = []; legendStrings = [];
for ii = 2:size(obj.agents, 1) for ii = 2:size(obj.agents, 1)
for jj = 1:(ii - 1) for jj = 1:(ii - 1)
@@ -31,7 +35,7 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)"); xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Obstacles"); title(obj.hf.Children(1).Children(1), "Obstacles");
hold(obj.hf.Children(1).Children(1), "on"); hold(obj.hf.Children(1).Children(1), "on");
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)), :)'); obj.obsPlot = plot(obj.barriers((nCA + 1):(nCA + nObs), :)');
legendStrings = []; legendStrings = [];
for ii = 1:size(obj.obstacles, 1) for ii = 1:size(obj.obstacles, 1)
for jj = 1:size(obj.agents, 1) for jj = 1:size(obj.agents, 1)
@@ -47,8 +51,13 @@ function obj = plotH(obj)
xlabel(obj.hf.Children(1).Children(1), "Time (s)"); xlabel(obj.hf.Children(1).Children(1), "Time (s)");
title(obj.hf.Children(1).Children(1), "Domain"); title(obj.hf.Children(1).Children(1), "Domain");
hold(obj.hf.Children(1).Children(1), "on"); hold(obj.hf.Children(1).Children(1), "on");
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)'); obj.domPlot = plot(obj.barriers((nCA + nObs + 1):(nCA + nObs + nDom), :)');
legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], "Location", "bestoutside"); 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");
hold(obj.hf.Children(1).Children(2), "off"); hold(obj.hf.Children(1).Children(2), "off");
nexttile(obj.hf.Children(1)); nexttile(obj.hf.Children(1));
+9
View File
@@ -11,6 +11,10 @@ function [obj] = run(obj)
if obj.makeVideo if obj.makeVideo
v = obj.setupVideoWriter(); v = obj.setupVideoWriter();
v.open(); v.open();
% Write initialization state frame in to video
I = getframe(obj.f);
v.writeVideo(I);
end end
end end
@@ -34,6 +38,11 @@ function [obj] = run(obj)
obj = obj.lesserNeighbor(); obj = obj.lesserNeighbor();
end end
% Log constraint adjacency for this timestep
if coder.target('MATLAB')
obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
end
% Moving % Moving
% Iterate over agents to simulate their unconstrained motion % Iterate over agents to simulate their unconstrained motion
for jj = 1:size(obj.agents, 1) for jj = 1:size(obj.agents, 1)
+2 -1
View File
@@ -20,6 +20,7 @@ function obj = teardown(obj)
out.dampingCoeff = obj.dampingCoeff; out.dampingCoeff = obj.dampingCoeff;
out.useDoubleIntegrator = obj.useDoubleIntegrator; out.useDoubleIntegrator = obj.useDoubleIntegrator;
out.useFixedTopology = obj.useFixedTopology; out.useFixedTopology = obj.useFixedTopology;
out.constraintAdjacency = obj.constraintAdjacencyHist(:, :, 1:(end - 1));
for ii = 1:size(obj.agents, 1) for ii = 1:size(obj.agents, 1)
out.agent(ii).pos = squeeze(obj.posHist(ii, 1:(end - 1), 1:3)); 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).vel = squeeze(obj.velHist(ii, 1:(end - 1), 1:3));
@@ -39,11 +40,11 @@ function obj = teardown(obj)
obj.timestepIndex = NaN; obj.timestepIndex = NaN;
obj.maxIter = NaN; obj.maxIter = NaN;
obj.domain = rectangularPrism; obj.domain = rectangularPrism;
obj.objective = sensingObjective;
obj.obstacles = cell(0, 1); obj.obstacles = cell(0, 1);
obj.agents = cell(0, 1); obj.agents = cell(0, 1);
obj.adjacency = NaN; obj.adjacency = NaN;
obj.constraintAdjacencyMatrix = NaN; obj.constraintAdjacencyMatrix = NaN;
obj.constraintAdjacencyHist = [];
obj.partitioning = NaN; obj.partitioning = NaN;
obj.performance = 0; obj.performance = 0;
obj.barrierGain = NaN; obj.barrierGain = NaN;
+7 -5
View File
@@ -61,13 +61,15 @@ function [obj] = updatePlots(obj)
end end
% Update h function plots % Update h function plots
for ii = 1:size(obj.caPlot, 1) nCA = size(obj.caPlot, 1);
obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex); nObs = size(obj.obsPlot, 1);
for ii = 1:nCA
obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
end end
for ii = 1:size(obj.obsPlot, 1) for ii = 1:nObs
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex); obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, obj.timestepIndex);
end end
for ii = 1:size(obj.domPlot, 1) for ii = 1:size(obj.domPlot, 1)
obj.domPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1) + size(obj.obsPlot, 1), obj.timestepIndex); obj.domPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + nObs + ii, obj.timestepIndex);
end end
end end
+4 -5
View File
@@ -7,11 +7,11 @@ function validate(obj)
%% Communications Network Validators %% Communications Network Validators
if max(conncomp(graph(obj.adjacency))) ~= 1 if max(conncomp(graph(obj.adjacency))) ~= 1
warning("Network is not connected"); error("Network is not connected");
end end
if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all") if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all")
warning("Eliminated network connections that were necessary"); error("Eliminated network connections that were necessary");
end end
%% Obstacle Validators %% Obstacle Validators
@@ -20,10 +20,9 @@ function validate(obj)
for kk = 1:size(obj.agents, 1) for kk = 1:size(obj.agents, 1)
P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner); P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner);
d = obj.agents{kk}.pos - P; d = obj.agents{kk}.pos - P;
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 - 1e-3
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 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
end end
end end
end end
end end
+17 -6
View File
@@ -5,29 +5,40 @@ function writeInits(obj)
arguments (Output) arguments (Output)
end 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 % Collect agent parameters
collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents); collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents); alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents); betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents); alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents); betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents); comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents); initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false)); 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 % Combine with simulation parameters
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ... inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter + 1, "minAlt", obj.minAlt, ...
"discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ... "discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
"sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ... "sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ... "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", numInputObs, ...
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ... "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ... "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
"alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ... "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
... % ^^^ PARAMETERS ^^^ | vvv STATES vvv ... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
"pos", pos); % still needs obstacle states and objective state "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(:)));
% Save all parameters to output file % Save all parameters to output file
initsFile = strcat(obj.artifactName, "_miSimInits"); initsFile = strcat(obj.artifactName, "_miSimInits");
initsFile = fullfile(matlab.project.rootProject().RootFolder, "sandbox", initsFile); initsFile = fullfile(matlab.project.rootProject().RootFolder, "sandbox", initsFile);
save(initsFile, "-struct", "inits"); save(initsFile, "-struct", "inits");
end end
+12 -5
View File
@@ -1,4 +1,4 @@
function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum) function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum, objectiveMu, objectiveSigma)
arguments (Input) arguments (Input)
obj (1,1) {mustBeA(obj, "sensingObjective")}; obj (1,1) {mustBeA(obj, "sensingObjective")};
objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")}; objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")};
@@ -6,6 +6,8 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
discretizationStep (1, 1) double = 1; discretizationStep (1, 1) double = 1;
protectedRange (1, 1) double = 1; protectedRange (1, 1) double = 1;
sensorPerformanceMinimum (1, 1) double = 1e-6; sensorPerformanceMinimum (1, 1) double = 1e-6;
objectiveMu (:, 2) double = NaN(1, 2);
objectiveSigma (:, 2, 2) double = NaN(1, 2, 2);
end end
arguments (Output) arguments (Output)
obj (1,1) {mustBeA(obj, "sensingObjective")}; obj (1,1) {mustBeA(obj, "sensingObjective")};
@@ -36,9 +38,14 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
obj.values = obj.values ./ max(obj.values, [], "all"); obj.values = obj.values ./ max(obj.values, [], "all");
% store ground position % store ground position
idx = obj.values == 1; idx = obj.values == 1;
obj.groundPos = [obj.X(idx), obj.Y(idx)]; if any(isnan(objectiveMu))
obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow) 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;
assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective") assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective");
end end
+3 -3
View File
@@ -11,16 +11,16 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
% Set random objective position % Set random objective position
mu = domain.minCorner; mu = domain.minCorner;
while domain.distance(mu) < protectedRange while domain.distance(mu) < protectedRange * 1.01
mu = domain.random(); mu = domain.random();
end end
% Set random distribution parameters % Set random distribution parameters
sig = [2 + rand * 2, 1; 1, 2 + rand * 2]; sig = reshape([2 + rand * 2, 1; 1, 2 + rand * 2], [1 2 2]);
% Set up random bivariate normal distribution function % Set up random bivariate normal distribution function
objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig); objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig);
% Regular initialization % Regular initialization
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange); obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange, 1e-6, mu(1:2), sig);
end end
+2 -1
View File
@@ -2,7 +2,8 @@ classdef sensingObjective
% Sensing objective definition parent class % Sensing objective definition parent class
properties (SetAccess = private, GetAccess = public) properties (SetAccess = private, GetAccess = public)
label = ""; label = "";
groundPos = [NaN, NaN]; groundPos = NaN(1, 2);
objectiveSigma = NaN(1, 2, 2);
discretizationStep = NaN; discretizationStep = NaN;
X = []; X = [];
Y = []; Y = [];
+1 -1
View File
@@ -164,7 +164,7 @@ class UAVRunner(BasicRunner):
# Retry connection up to 10 times (~30 seconds total) # Retry connection up to 10 times (~30 seconds total)
reader, writer = None, None reader, writer = None, None
for attempt in range(10): for attempt in range(100):
try: try:
reader, writer = await asyncio.wait_for( reader, writer = await asyncio.wait_for(
asyncio.open_connection(self.server_ip, self.server_port), asyncio.open_connection(self.server_ip, self.server_port),
+3 -3
View File
@@ -28,11 +28,11 @@ environments:
port: 5000 port: 5000
testbed: testbed:
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP) # AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
mavlink: mavlink:
ip: "192.168.32.26" ip: "192.168.32.26"
port: 14550 port: 14550
# Controller runs on host machine (192.168.109.1 from E-VM perspective) # Controller runs on host machine (192.168.X.1, generally)
controller: controller:
ip: "192.168.109.1" ip: "192.168.112.1"
port: 5000 port: 5000
+3 -3
View File
@@ -28,11 +28,11 @@ environments:
port: 5000 port: 5000
testbed: testbed:
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP) # AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
mavlink: mavlink:
ip: "192.168.32.26" ip: "192.168.32.26"
port: 14550 port: 14550
# Controller runs on host machine (192.168.109.1 from E-VM perspective) # Controller runs on host machine (192.168.X.1, generally)
controller: controller:
ip: "192.168.109.1" ip: "192.168.112.1"
port: 5000 port: 5000
+1 -1
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 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
5, 100, 30.0, 0.1, 2.0, 2.0, 100, 3, "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 1, 50, 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, "10.0, 10.0, 50.0, 40.0, 15.0, 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 5 1 100 50 30.0 35.0 0.1 2.0 2.0 6 100 1 3 1 5.0, 5.0 8.0, 8.0 25.0, 25.0 35.0, 35.0 80.0, 80.0 80.0, 50.0 0.25, 0.25 0.25, 1.0 5.0, 5.0 8.0, 25.0 0.1, 0.1 0.1, 0.02 0.0, 0.0, 0.0 80.0, 80.0, 80.0 100.0, 100.0, 100.0 55.0, 55.0 60.0, 80.0, 45.0, 70.0 40, 25, 25, 40 70, 15, 15, 20, 20, 15, 15, 70 0.15 15.0, 10.0, 40.0, 5.0, 10.0, 45.0 10.0, 10.0, 50.0, 40.0, 15.0, 45.0 1 8 1.0, 25.0, 0.0 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 30.0, 30.0, 50.0 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 1 0 2.0 1
+2
View File
@@ -0,0 +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
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+118 -11
View File
@@ -7,34 +7,47 @@ coder.extrinsic('disp', 'readScenarioCsv');
% Maximum clients supported (one initial position per UAV) % Maximum clients supported (one initial position per UAV)
MAX_CLIENTS = 4; MAX_CLIENTS = 4;
MAX_TARGETS = MAX_CLIENTS; % Three waypoints per UAV: one axis-aligned move per dimension (taxicab flyout/flyback)
MAX_TARGETS = MAX_CLIENTS * 3;
% Taxicab flyout/flyback only supports exactly 2 UAVs
if numClients ~= int32(2)
error('Taxicab flyout/flyback requires exactly 2 UAVs');
end
% Allocate targets array (MAX_TARGETS x 3) % Allocate targets array (MAX_TARGETS x 3)
targets = zeros(MAX_TARGETS, 3); targets = zeros(MAX_TARGETS, 3);
numWaypoints = int32(0); numWaypoints = int32(0);
totalLoaded = int32(0); % pre-declare type for coder.ceval %#ok<NASGU> totalLoaded = int32(0); % pre-declare type for coder.ceval %#ok<NASGU>
% Load initial UAV positions from scenario CSV % Experiment start positions from scenario CSV (N x 3)
scenarioPositions = zeros(MAX_CLIENTS, 3);
% Load experiment start positions from scenario CSV
if coder.target('MATLAB') if coder.target('MATLAB')
disp('Loading initial positions from scenario.csv (simulation)...'); disp('Loading initial positions from scenario.csv (simulation)...');
tmpSim = miSim; tmpSim = miSim;
sc = tmpSim.readScenarioCsv('aerpaw/config/scenario.csv'); sc = tmpSim.readScenarioCsv('aerpaw/config/scenario.csv');
flatPos = double(sc.initialPositions); % 1×(3*N) flat vector flatPos = double(sc.initialPositions); % 1×(3*N) flat vector
posMatrix = reshape(flatPos, 3, [])'; % N×3, same layout as initializeFromCsv posMatrix = reshape(flatPos, 3, [])'; % N×3
totalLoaded = int32(size(posMatrix, 1)); totalLoaded = int32(size(posMatrix, 1));
scenarioPositions(1:totalLoaded, :) = posMatrix;
% MATLAB path: send directly to scenario positions in one waypoint
targets(1:totalLoaded, :) = posMatrix; targets(1:totalLoaded, :) = posMatrix;
numWaypoints = int32(1); numWaypoints = int32(1);
disp(['Loaded ', num2str(double(totalLoaded)), ' initial positions']); disp(['Loaded ', num2str(double(totalLoaded)), ' initial positions']);
else else
coder.cinclude('controller_impl.h'); coder.cinclude('controller_impl.h');
filename = ['config/scenario.csv', char(0)]; filename = ['config/scenario.csv', char(0)];
% Load into targets temporarily; copy to scenarioPositions below
totalLoaded = coder.ceval('loadInitialPositions', coder.ref(filename), ... totalLoaded = coder.ceval('loadInitialPositions', coder.ref(filename), ...
coder.ref(targets), int32(MAX_TARGETS)); coder.ref(targets), int32(MAX_TARGETS));
numWaypoints = totalLoaded / int32(numClients); scenarioPositions(1:totalLoaded, :) = targets(1:totalLoaded, :);
numWaypoints = int32(3);
end end
% Load guidance scenario from CSV (parameters for guidance_step) % Load guidance scenario from CSV (parameters for guidance_step)
NUM_SCENARIO_PARAMS = 45; NUM_SCENARIO_PARAMS = 48;
MAX_OBSTACLES_CTRL = int32(8); MAX_OBSTACLES_CTRL = int32(8);
scenarioParams = zeros(1, NUM_SCENARIO_PARAMS); scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
obstacleMin = zeros(MAX_OBSTACLES_CTRL, 3); obstacleMin = zeros(MAX_OBSTACLES_CTRL, 3);
@@ -68,6 +81,46 @@ for i = 1:numClients
end end
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
% ---- Build taxicab flyout waypoints ------------------------------------------
% Determine which UAV has the higher final altitude; it moves Z first so it
% clears vertical separation before the lower UAV converges on the same X/Y.
% Higher UAV order: Z Y X
% Lower UAV order: X Y Z
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
hBase = double(higherIdx - 1) * double(numWaypoints);
lBase = double(lowerIdx - 1) * double(numWaypoints);
% Higher UAV: Z first
targets(hBase + 1, :) = [initialPositions(higherIdx,1), initialPositions(higherIdx,2), scenarioPositions(higherIdx,3)];
targets(hBase + 2, :) = [initialPositions(higherIdx,1), scenarioPositions(higherIdx,2), scenarioPositions(higherIdx,3)];
targets(hBase + 3, :) = scenarioPositions(higherIdx, :);
% Lower UAV: X first
targets(lBase + 1, :) = [scenarioPositions(lowerIdx,1), initialPositions(lowerIdx,2), initialPositions(lowerIdx,3)];
targets(lBase + 2, :) = [scenarioPositions(lowerIdx,1), scenarioPositions(lowerIdx,2), initialPositions(lowerIdx,3)];
targets(lBase + 3, :) = scenarioPositions(lowerIdx, :);
end
% ------------------------------------------------------------------------------
% Waypoint loop: send each waypoint to all clients, wait for all to arrive % Waypoint loop: send each waypoint to all clients, wait for all to arrive
for w = 1:numWaypoints for w = 1:numWaypoints
% Send TARGET for waypoint w to each client % Send TARGET for waypoint w to each client
@@ -78,7 +131,7 @@ for w = 1:numWaypoints
target = targets(targetIdx, :); target = targets(targetIdx, :);
if coder.target('MATLAB') if coder.target('MATLAB')
disp([datestr(now, 'HH:MM:SS'), ' Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ... disp(['Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]); num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]);
else else
coder.ceval('sendTarget', int32(i), coder.ref(target)); coder.ceval('sendTarget', int32(i), coder.ref(target));
@@ -103,8 +156,13 @@ for w = 1:numWaypoints
end end
% ---- Phase 2: miSim guidance loop ---------------------------------------- % ---- Phase 2: miSim guidance loop ----------------------------------------
% Guidance parameters (adjust here and recompile as needed) % Number of guidance steps comes from maxIter in scenario.csv (scenarioParams(2))
MAX_GUIDANCE_STEPS = int32(100); % number of guidance iterations % 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
% Enter guidance mode on all clients % Enter guidance mode on all clients
if ~coder.target('MATLAB') if ~coder.target('MATLAB')
@@ -117,14 +175,18 @@ if ~coder.target('MATLAB')
coder.ceval('sendRequestPositions', int32(numClients)); coder.ceval('sendRequestPositions', int32(numClients));
coder.ceval('recvPositions', int32(numClients), coder.ref(positions), int32(MAX_CLIENTS)); coder.ceval('recvPositions', int32(numClients), coder.ref(positions), int32(MAX_CLIENTS));
else else
% Simulation: seed positions from CSV waypoints so agents don't start at origin % Simulation: seed positions from scenario positions so agents don't start at origin
positions(1:totalLoaded, :) = targets(1:totalLoaded, :); positions(1:totalLoaded, :) = scenarioPositions(1:totalLoaded, :);
end end
guidance_step(positions(1:numClients, :), true, ... guidance_step(positions(1:numClients, :), true, ...
scenarioParams, obstacleMin, obstacleMax, numObstacles); scenarioParams, obstacleMin, obstacleMax, numObstacles);
% Main guidance loop (event-triggered) % Main guidance loop (event-triggered)
for step = 1:MAX_GUIDANCE_STEPS 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 % Run one guidance step: feed current GPS positions in, get targets out
nextPositions = guidance_step(positions(1:numClients, :), false, ... nextPositions = guidance_step(positions(1:numClients, :), false, ...
scenarioParams, obstacleMin, obstacleMax, numObstacles); scenarioParams, obstacleMin, obstacleMax, numObstacles);
@@ -135,7 +197,7 @@ for step = 1:MAX_GUIDANCE_STEPS
if ~coder.target('MATLAB') if ~coder.target('MATLAB')
coder.ceval('sendTarget', int32(i), coder.ref(target)); coder.ceval('sendTarget', int32(i), coder.ref(target));
else else
disp([datestr(now, 'HH:MM:SS'), ' [guidance] target UAV ', num2str(i), ': ', num2str(target)]); disp(['[step ', num2str(step), '] target UAV ', num2str(i), ': ', num2str(target)]);
end end
end end
@@ -164,6 +226,51 @@ if ~coder.target('MATLAB')
% last guidance navigation and is back in sequential (ACK/READY) mode. % last guidance navigation and is back in sequential (ACK/READY) mode.
coder.ceval('waitForAllMessageType', int32(numClients), ... coder.ceval('waitForAllMessageType', int32(numClients), ...
int32(MESSAGE_TYPE.ACK)); 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
% --------------------------------------------------------------------------
% ---- Taxicab flyback: return each UAV to its takeoff-pad position ---------
% The UAV that ended guidance at the higher altitude moves Z last (X Y Z)
% so it stays high while the lower UAV descends first, maintaining separation
% as both converge back on their respective home X/Y positions.
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
hRetBase = double(higherRetIdx - 1) * double(NUM_RETURN_WP);
lRetBase = double(lowerRetIdx - 1) * double(NUM_RETURN_WP);
% Higher post-guidance UAV: X Y Z (descend last)
returnTargets(hRetBase + 1, :) = [initialPositions(higherRetIdx,1), positions(higherRetIdx,2), positions(higherRetIdx,3)];
returnTargets(hRetBase + 2, :) = [initialPositions(higherRetIdx,1), initialPositions(higherRetIdx,2), positions(higherRetIdx,3)];
returnTargets(hRetBase + 3, :) = initialPositions(higherRetIdx, :);
% Lower post-guidance UAV: Z Y X (descend first)
returnTargets(lRetBase + 1, :) = [positions(lowerRetIdx,1), positions(lowerRetIdx,2), initialPositions(lowerRetIdx,3)];
returnTargets(lRetBase + 2, :) = [positions(lowerRetIdx,1), initialPositions(lowerRetIdx,2), initialPositions(lowerRetIdx,3)];
returnTargets(lRetBase + 3, :) = initialPositions(lowerRetIdx, :);
for w = 1:NUM_RETURN_WP
for i = 1:numClients
retIdx = double(i - 1) * double(NUM_RETURN_WP) + w;
retTarget = returnTargets(retIdx, :);
coder.ceval('sendTarget', int32(i), coder.ref(retTarget));
end
coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.ACK));
coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.READY));
end
else
disp('Taxicab return (simulation): UAVs commanded back to takeoff positions.');
end end
% -------------------------------------------------------------------------- % --------------------------------------------------------------------------
+13 -3
View File
@@ -29,6 +29,9 @@ function nextPositions = guidance_step(currentPositions, isInit, ...
% 39-40 objectivePos % 39-40 objectivePos
% 41-44 objectiveVar (2x2, col-major) % 41-44 objectiveVar (2x2, col-major)
% 45 sensorPerformanceMinimum % 45 sensorPerformanceMinimum
% 46 useDoubleIntegrator
% 47 dampingCoeff
% 48 useFixedTopology
% obstacleMin (MAX_OBSTACLES × 3) double column-major obstacle corners (compiled path) % obstacleMin (MAX_OBSTACLES × 3) double column-major obstacle corners (compiled path)
% obstacleMax (MAX_OBSTACLES × 3) double % obstacleMax (MAX_OBSTACLES × 3) double
% numObstacles (1,1) int32 actual obstacle count % numObstacles (1,1) int32 actual obstacle count
@@ -94,6 +97,9 @@ if isInit
OBJECTIVE_GROUND_POS = scenarioParams(39:40); OBJECTIVE_GROUND_POS = scenarioParams(39:40);
OBJECTIVE_VAR = reshape(scenarioParams(41:44), 2, 2); OBJECTIVE_VAR = reshape(scenarioParams(41:44), 2, 2);
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(45); SENSOR_PERFORMANCE_MINIMUM = scenarioParams(45);
USE_DOUBLE_INTEGRATOR = logical(scenarioParams(46));
DAMPING_COEFF = scenarioParams(47);
USE_FIXED_TOPOLOGY = logical(scenarioParams(48));
% --- Build domain geometry --- % --- Build domain geometry ---
dom = rectangularPrism; dom = rectangularPrism;
@@ -146,7 +152,8 @@ if isInit
% --- Initialise simulation (plots and video disabled) --- % --- Initialise simulation (plots and video disabled) ---
sim = miSim; sim = miSim;
sim = sim.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ... sim = sim.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false); MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
end end
% On the init call return current positions unchanged % On the init call return current positions unchanged
@@ -176,7 +183,9 @@ else
sim.timestepIndex = sim.timestepIndex + 1; sim.timestepIndex = sim.timestepIndex + 1;
% 3. Update communications topology (Lesser Neighbour Assignment) % 3. Update communications topology (Lesser Neighbour Assignment)
sim = sim.lesserNeighbor(); if ~sim.useFixedTopology
sim = sim.lesserNeighbor();
end
% 4. Compute Voronoi partitioning % 4. Compute Voronoi partitioning
sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective); sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
@@ -184,7 +193,8 @@ else
% 5. Unconstrained gradient-ascent step for each agent % 5. Unconstrained gradient-ascent step for each agent
for ii = 1:size(sim.agents, 1) for ii = 1:size(sim.agents, 1)
sim.agents{ii} = sim.agents{ii}.run(sim.domain, sim.partitioning, ... sim.agents{ii} = sim.agents{ii}.run(sim.domain, sim.partitioning, ...
sim.timestepIndex, ii, sim.agents); sim.timestepIndex, ii, sim.agents, ...
sim.useDoubleIntegrator, sim.dampingCoeff, sim.timestep);
end end
% 6. Apply CBF safety filter (collision / comms / domain constraints via QP) % 6. Apply CBF safety filter (collision / comms / domain constraints via QP)
+81 -19
View File
@@ -16,6 +16,44 @@
static int serverSocket = -1; static int serverSocket = -1;
static std::vector<int> clientSockets; 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 initSockets() {}
void cleanupSockets() {} void cleanupSockets() {}
@@ -186,7 +224,10 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
// 35-37: domainMax (east, north, up) // 35-37: domainMax (east, north, up)
// 38-39: objectivePos (east, north) // 38-39: objectivePos (east, north)
// 40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22) // 40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
// 44 : sensorPerformanceMinimum // 44 : sensorPerformanceMinimum (CSV column 18)
// 45 : useDoubleIntegrator (CSV column 23; 0=single-integrator, 1=double-integrator)
// 46 : dampingCoeff (CSV column 24)
// 47 : useFixedTopology (CSV column 25; 0=dynamic lesser-neighbor, 1=fixed)
// Returns 1 on success, 0 on failure. // Returns 1 on success, 0 on failure.
int loadScenario(const char* filename, double* params) { int loadScenario(const char* filename, double* params) {
char line[4096]; char line[4096];
@@ -198,8 +239,8 @@ int loadScenario(const char* filename, double* params) {
char* fields[32]; char* fields[32];
int nf = splitCSVRow(copy, fields, 32); int nf = splitCSVRow(copy, fields, 32);
if (nf < 19) { if (nf < 26) {
fprintf(stderr, "loadScenario: expected >=19 columns, got %d\n", nf); fprintf(stderr, "loadScenario: expected >=26 columns, got %d\n", nf);
return 0; return 0;
} }
@@ -290,6 +331,24 @@ int loadScenario(const char* filename, double* params) {
params[44] = 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[45] = atof(trimField(tmp));
}
// dampingCoeff: column 24
{
char tmp[64]; strncpy(tmp, fields[24], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[46] = atof(trimField(tmp));
}
// useFixedTopology: column 25
{
char tmp[64]; strncpy(tmp, fields[25], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
params[47] = atof(trimField(tmp));
}
printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g]\n", printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g]\n",
params[32], params[33], params[34], params[35], params[36], params[37]); params[32], params[33], params[34], params[35], params[36], params[37]);
return 1; return 1;
@@ -430,18 +489,22 @@ static const char* messageTypeName(uint8_t msgType) {
} }
} }
// Send a single-byte message type to a client // Send a single-byte message type to a client (no logging)
int sendMessageType(int clientId, int msgType) { static int sendMessageTypeRaw(int clientId, int msgType) {
if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0; if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0;
uint8_t msg = (uint8_t)msgType; uint8_t msg = (uint8_t)msgType;
ssize_t sent = send(clientSockets[clientId - 1], &msg, 1, 0); ssize_t sent = send(clientSockets[clientId - 1], &msg, 1, 0);
if (sent != 1) { if (sent != 1) {
std::cerr << "Send failed for client " << clientId << "\n"; std::cerr << "Send failed for client " << clientId << "\n";
return 0; return 0;
} }
return 1;
}
std::cout << "Sent " << messageTypeName(msg) << " to client " << clientId << "\n"; // 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";
return 1; return 1;
} }
@@ -460,13 +523,7 @@ int sendTarget(int clientId, const double* coords) {
return 0; return 0;
} }
// Timestamp std::cout << logPrefix() << "Sent TARGET to client " << clientId << ": "
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"; << coords[0] << "," << coords[1] << "," << coords[2] << "\n";
return 1; return 1;
} }
@@ -514,31 +571,36 @@ int waitForAllMessageType(int numClients, int expectedType) {
return 0; return 0;
} }
std::cout << "Received " << messageTypeName(msgType) << " from client " << (i + 1) << "\n";
if (msgType == expected) { if (msgType == expected) {
completed[i] = true; completed[i] = true;
completedCount++; 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; return 1;
} }
// Broadcast GUIDANCE_TOGGLE to all clients // Broadcast GUIDANCE_TOGGLE to all clients
void sendGuidanceToggle(int numClients) { void sendGuidanceToggle(int numClients) {
for (int i = 1; i <= numClients; i++) { for (int i = 1; i <= numClients; i++) {
sendMessageType(i, 6); // GUIDANCE_TOGGLE = 6 sendMessageTypeRaw(i, 6); // GUIDANCE_TOGGLE = 6
} }
std::cout << logPrefix() << "Sent GUIDANCE_TOGGLE to clients\n";
} }
// Send REQUEST_POSITION to all clients // Send REQUEST_POSITION to all clients
int sendRequestPositions(int numClients) { int sendRequestPositions(int numClients) {
for (int i = 1; i <= numClients; i++) { for (int i = 1; i <= numClients; i++) {
if (!sendMessageType(i, 7)) return 0; // REQUEST_POSITION = 7 if (!sendMessageTypeRaw(i, 7)) return 0; // REQUEST_POSITION = 7
} }
std::cout << logPrefix() << "Sent REQUEST_POSITION to clients\n";
return 1; return 1;
} }
@@ -573,7 +635,7 @@ int recvPositions(int numClients, double* positions, int maxClients) {
positions[i + 1 * maxClients] = coords[1]; // north (y) positions[i + 1 * maxClients] = coords[1]; // north (y)
positions[i + 2 * maxClients] = coords[2]; // up (z) positions[i + 2 * maxClients] = coords[2]; // up (z)
std::cout << "Position from client " << (i + 1) << ": " std::cout << logPrefix() << "Position from client " << (i + 1) << ": "
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n"; << coords[0] << "," << coords[1] << "," << coords[2] << "\n";
} }
return 1; return 1;
+5 -1
View File
@@ -30,7 +30,10 @@ int loadTargets(const char* filename, double* targets, int maxClients);
// 38-39 objectivePos // 38-39 objectivePos
// 40-43 objectiveVar (2x2 col-major) // 40-43 objectiveVar (2x2 col-major)
// 44 sensorPerformanceMinimum // 44 sensorPerformanceMinimum
#define NUM_SCENARIO_PARAMS 45 // 45 useDoubleIntegrator (0=single-integrator, 1=double-integrator)
// 46 dampingCoeff
// 47 useFixedTopology (0=dynamic lesser-neighbor, 1=fixed)
#define NUM_SCENARIO_PARAMS 48
#define MAX_CLIENTS_PER_PARAM 4 #define MAX_CLIENTS_PER_PARAM 4
// Maximum number of obstacles (upper bound for pre-allocated arrays). // Maximum number of obstacles (upper bound for pre-allocated arrays).
#define MAX_OBSTACLES 8 #define MAX_OBSTACLES 8
@@ -59,6 +62,7 @@ int sendTarget(int clientId, const double* coords);
int waitForAllMessageType(int numClients, int expectedType); int waitForAllMessageType(int numClients, int expectedType);
// Guidance loop operations // Guidance loop operations
void setGuidanceStep(int step, int totalSteps); // call at the top of each guidance iteration
void sendGuidanceToggle(int numClients); void sendGuidanceToggle(int numClients);
int sendRequestPositions(int numClients); int sendRequestPositions(int numClients);
int recvPositions(int numClients, double* positions, int maxClients); // column-major maxClients x 3 int recvPositions(int numClients, double* positions, int maxClients); // column-major maxClients x 3
+2 -1
View File
@@ -12,4 +12,5 @@ cp ../scripts/startRadio.sh /root/Profiles/ProfileScripts/Radio/.
cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/. cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml" 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 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 -3
View File
@@ -1,7 +1,8 @@
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel) function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
arguments (Input) arguments (Input)
logDirs (1, 1) string; logDirs (1, 1) string;
seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
plotWholeFlight (1, 1) logical = false;
end end
arguments (Output) arguments (Output)
f (1, 1) matlab.ui.Figure; f (1, 1) matlab.ui.Figure;
@@ -28,6 +29,7 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
logDirs = dir(logDirs); logDirs = dir(logDirs);
logDirs = logDirs(3:end); logDirs = logDirs(3:end);
logDirs = logDirs([logDirs.isdir] == 1); logDirs = logDirs([logDirs.isdir] == 1);
logDirs = logDirs(~startsWith({logDirs.name}, "controller_"));
G = cell(size(logDirs)); G = cell(size(logDirs));
for ii = 1:size(logDirs, 1) for ii = 1:size(logDirs, 1)
@@ -48,8 +50,10 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last"); stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
% % Plot whole flight, including setup/cleanup % % Plot whole flight, including setup/cleanup
% startIdx = 1; if plotWholeFlight
% stopIdx = length(verticalSpeed); startIdx = 1;
stopIdx = length(verticalSpeed);
end
% Convert LLA trajectory data to ENU for external analysis % Convert LLA trajectory data to ENU for external analysis
% NaN out entries outside the algorithm flight range so they don't plot % NaN out entries outside the algorithm flight range so they don't plot
@@ -57,6 +61,27 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
enu(startIdx:stopIdx, :) = lla2enu([G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx)], lla0, "flat"); enu(startIdx:stopIdx, :) = lla2enu([G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx)], lla0, "flat");
enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]); enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
G{ii} = [G{ii}, enu]; 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));
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 % 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); 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);
+32
View File
@@ -0,0 +1,32 @@
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
+16 -5
View File
@@ -2,7 +2,6 @@ function R = readRadioLogs(logPath)
arguments (Input) arguments (Input)
logPath (1, 1) string {isfolder(logPath)}; logPath (1, 1) string {isfolder(logPath)};
end end
arguments (Output) arguments (Output)
R (:, 8) table; R (:, 8) table;
end end
@@ -31,14 +30,26 @@ function R = readRadioLogs(logPath)
end end
fid = fopen(filepath, 'r'); fid = fopen(filepath, 'r');
% Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value) % Skip header lines: some files have 2 tail-error lines + 1 column
for k = 1:3 % header ("tx_uav_id,value"), others start with data immediately.
fgetl(fid); % 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);
end end
data = textscan(fid, '[%26c] %d,%f'); data = textscan(fid, '[%26c] %d,%f');
fclose(fid); fclose(fid);
ts = datetime(data{1}, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS'); ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
txId = int32(data{2}); txId = int32(data{2});
val = data{3}; val = data{3};
+23 -2
View File
@@ -1,9 +1,30 @@
%% Plot AERPAW logs (trajectory, radio) %% 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", "two_around_wall"); % Define path to results copied from AERPAW platform
% 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
% Plot GPS logged data and scenario information (domain, objective, obstacles) % Plot GPS logged data and scenario information (domain, objective, obstacles)
seaToGroundLevel = 110; % measured approximately from USGS national map viewer seaToGroundLevel = 110; % measured approximately from USGS national map viewer
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel); plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
% Plot radio statistics % Plot radio statistics
[fRadio, R] = plotRadioLogs(resultsPath); [fRadio, R] = plotRadioLogs(resultsPath);
@@ -21,7 +42,7 @@ makeVideo = true;
% Define scenario according to CSV specification % Define scenario according to CSV specification
domain = rectangularPrism; domain = rectangularPrism;
domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain"); domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum); domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [1, 2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
agents = cell(size(params.initialPositions, 2) / 3, 1); agents = cell(size(params.initialPositions, 2) / 3, 1);
for ii = 1:size(agents, 1) for ii = 1:size(agents, 1)
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="initializeFromInits.m" type="File"/>
@@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="plotFromSimHist.m" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -0,0 +1,6 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>
@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="readControllerLogs.m" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test4" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test13" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="t1" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test14" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test11" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test6" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test3" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test10" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="test12" type="File"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info/>
@@ -1,2 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>
+12 -4
View File
@@ -34,8 +34,15 @@ classdef parametricTestSuite < matlab.unittest.TestCase
% Define scenario according to CSV specification % Define scenario according to CSV specification
tc.domain = tc.domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), tc.domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum); 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
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(objectivePos, objectiveSigma), tc.domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum, objectivePos, objectiveSigma);
agents = cell(size(params.initialPositions, 2) / 3, 1); agents = cell(size(params.initialPositions, 2) / 3, 1);
for ii = 1:size(agents, 1) for ii = 1:size(agents, 1)
agents{ii} = agent; agents{ii} = agent;
@@ -81,7 +88,8 @@ classdef parametricTestSuite < matlab.unittest.TestCase
for ii = 1:size(params.timestep, 1) for ii = 1:size(params.timestep, 1)
% Set up square domain % Set up square domain
tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii)); objectiveCenter = [.75 * l, 0.75 * l];
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(objectiveCenter), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii), objectiveCenter);
% Initialize agents % Initialize agents
agents = cell(params.numAgents(ii), 1); agents = cell(params.numAgents(ii), 1);
@@ -150,7 +158,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
end end
% randomly shuffle agents to make the network more interesting (probably) % randomly shuffle agents to make the network more interesting (probably)
agents = agents(randperm(numel(agents))); agents = agents(randperm(numel(agents)));
% Set up obstacles % Set up obstacles
obstacles = cell(params.numObstacles(ii), 1); obstacles = cell(params.numObstacles(ii), 1);
+132 -10
View File
@@ -166,8 +166,8 @@ classdef test_miSim < matlab.unittest.TestCase
end end
% Initialize candidate agent collision geometry % Initialize candidate agent collision geometry
candidateGeometry = rectangularPrism; candidateGeometry = spherical;
candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION); candidateGeometry = candidateGeometry.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
% Initialize candidate agent sensor model % Initialize candidate agent sensor model
tc.sensor = tc.sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin)); tc.sensor = tc.sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
@@ -437,12 +437,12 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [7, 6]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent}; tc.agents = {agent};
geometry1 = rectangularPrism; geometry1 = spherical;
geometry1 = geometry1.initialize([[tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION); geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
% Initialize agent sensor model with fixed parameters % Initialize agent sensor model with fixed parameters
tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3); tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3);
@@ -466,7 +466,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [3, 7]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent; agent}; tc.agents = {agent; agent};
@@ -504,7 +504,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5.2195]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent; agent;}; tc.agents = {agent; agent;};
@@ -588,7 +588,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent; agent;}; tc.agents = {agent; agent;};
@@ -633,7 +633,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent; agent; agent; agent; agent;}; tc.agents = {agent; agent; agent; agent; agent;};
@@ -683,7 +683,7 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain"); tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective % make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange); tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
% Initialize agent collision geometry % Initialize agent collision geometry
tc.agents = {agent; agent; agent; agent; agent; agent; agent;}; tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
@@ -728,6 +728,128 @@ classdef test_miSim < matlab.unittest.TestCase
0, 0, 0, 1, 1, 1, 1; 0, 0, 0, 1, 1, 1, 1;
0, 0, 0, 0, 0, 1, 1; ])); 0, 0, 0, 0, 0, 1, 1; ]));
end end
function miSim_initializeFromInits(tc)
% Build a minimal valid simulation, write it to a matfile, reload
% via initializeFromInits, assert round-trip consistency, then
% delete the file. No plotting or video at any stage.
% Obstacles
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
tc.obstacles = cell(nGeom, 1);
for ii = 1:nGeom
badCandidate = true;
while badCandidate
tc.obstacles{ii} = rectangularPrism;
tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, ...
sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, ...
tc.domain, tc.minAlt);
if ~tc.obstacleCollisionCheck(tc.obstacles(1:(ii - 1)), tc.obstacles{ii})
badCandidate = false;
end
end
end
% Agents
nAgents = tc.minAgents;
tc.agents = cell(nAgents, 1);
tc.collisionRanges = tc.minCollisionRange + rand(nAgents, 1) * (tc.maxCollisionRange - tc.minCollisionRange);
tc.commsRanges = tc.minCommsRange + rand(nAgents, 1) * (tc.maxCommsRange - tc.minCommsRange);
for ii = 1:nAgents
initInvalid = true;
while initInvalid
if ii == 1
candidatePos = tc.domain.random();
candidatePos(3) = tc.minAlt + rand * 3;
while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
candidatePos = tc.domain.random();
candidatePos(3) = tc.minAlt + rand * 3;
end
else
candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.commsRanges(ii) / sqrt(2));
candidatePos(3) = tc.minAlt + rand * 3;
end
if ~tc.domain.contains(candidatePos), continue; end
if agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2), continue; end
% Connectivity check
connections = false(1, ii - 1);
for jj = 1:(ii - 1)
if norm(tc.agents{jj}.pos - candidatePos) <= min(tc.commsRanges([ii, jj]))
connections(jj) = true;
for kk = 1:size(tc.obstacles, 1)
if tc.obstacles{kk}.containsLine(tc.agents{jj}.pos, candidatePos)
connections(jj) = false;
end
end
end
end
if ii ~= 1 && ~any(connections), continue; end
geom = spherical;
geom = geom.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
tc.sensor = sigmoidSensor;
tc.sensor = tc.sensor.initialize( ...
tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), ...
tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), ...
tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), ...
tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
newAgent = agent;
newAgent = newAgent.initialize(candidatePos, geom, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize);
% Domain / obstacle / agent collision checks
violation = false;
for jj = 1:size(newAgent.collisionGeometry.vertices, 1)
if ~tc.domain.contains(newAgent.collisionGeometry.vertices(jj, 1:3))
violation = true; break;
end
end
if violation, continue; end
for kk = 1:size(tc.obstacles, 1)
if geometryIntersects(tc.obstacles{kk}, newAgent.collisionGeometry)
violation = true; break;
end
end
if violation, continue; end
for kk = 1:(ii - 1)
if geometryIntersects(tc.agents{kk}.collisionGeometry, newAgent.collisionGeometry)
violation = true; break;
end
end
if newAgent.pos(3) - newAgent.collisionGeometry.radius <= tc.minAlt
violation = true;
end
if violation, continue; end
initInvalid = false;
tc.agents{ii} = newAgent;
end
end
% Initialize first sim (no plots / video)
sim1 = miSim;
sim1 = sim1.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, ...
tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, false, false, ...
tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
% Write inits and build file path
sim1.writeInits();
initsFile = fullfile(matlab.project.rootProject().RootFolder, "sandbox", ...
strcat(sim1.artifactName, "_miSimInits.mat"));
% Load via initializeFromInits
sim2 = miSim;
sim2 = sim2.initializeFromInits(initsFile);
% Assertions
tc.assertEqual(size(sim2.agents, 1), size(sim1.agents, 1));
tc.assertEqual(sim2.maxIter, sim1.maxIter);
tc.assertEqual(sim2.barrierGain, sim1.barrierGain);
% Cleanup
delete(initsFile);
end
end end
methods methods
+6 -2
View File
@@ -4,12 +4,16 @@ function f = objectiveFunctionWrapper(center, sigma)
% composite objectives in particular % composite objectives in particular
arguments (Input) arguments (Input)
center (:, 2) double; center (:, 2) double;
sigma (2, 2) double = eye(2); sigma (:, 2, 2) double = reshape(eye(2), 1, 2, 2);
end end
arguments (Output) arguments (Output)
f (1, 1) {mustBeA(f, "function_handle")}; f (1, 1) {mustBeA(f, "function_handle")};
end end
f = @(x,y) sum(cell2mat(arrayfun(@(i) mvnpdf([x(:), y(:)], center(i,:), sigma), 1:size(center,1), "UniformOutput", false)), 2); if size(sigma, 1) == 1 && size(center, 1) > 1
sigma = repmat(sigma, size(center, 1), 1, 1);
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);
end end