organizing

.gitignore

@@ -4,7 +4,6 @@
 *.autosave
 *.slx.r*
 *.mdl.r*
-*.bak
 
 # Derived content-obscured files
 *.p

@miSim/constrainMotion.m

@@ -61,9 +61,7 @@ function [obj] = constrainMotion(obj)
     end
 
     idx = length(h(triu(true(size(h)), 1)));
-    if coder.target('MATLAB')
     obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
-    end
     idx = idx + 1;
 
     hObs = NaN(nAgents, size(obj.obstacles, 1));
@@ -86,9 +84,7 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    if coder.target('MATLAB')
     obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
-    end
     idx = idx + numel(hObs);
 
     % Set up domain constraints (walls and ceiling only)
@@ -132,12 +128,15 @@ function [obj] = constrainMotion(obj)
         b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
         kk = kk + 1;
 
-        if coder.target('MATLAB')
         obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
-        end
         idx = idx + 6;
     end
 
+    if coder.target('MATLAB')
+        % Save off h function values (logging only — not needed in compiled mode)
+        obj.h(:, obj.timestepIndex) = [h(triu(true(nAgents), 1)); reshape(hObs, [], 1); h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax;];
+    end
+
     % Add communication network constraints
     hComms = NaN(nAgents, nAgents);
     hComms(logical(eye(nAgents))) = 0;
@@ -165,10 +164,7 @@ function [obj] = constrainMotion(obj)
             end
         end
     end
-    
-    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.
     % Single-integrator constraint: A * v <= b

@miSim/initialize.m

@@ -109,6 +109,8 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
         % Prepare performance data store (at t = 0, all have 0 performance)
         obj.perf = [zeros(size(obj.agents, 1) + 1, 1), NaN(size(obj.agents, 1) + 1, size(obj.partitioningTimes, 1) - 1)];
 
+        % Prepare h function data store
+        obj.h = NaN(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2 + size(obj.agents, 1) * size(obj.obstacles, 1) + 6, size(obj.times, 1));
     end
 
     % Create initial partitioning
@@ -141,7 +143,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
         obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
         obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
 
-
         % Set up plots showing initialized state
         obj = obj.plot();
 

@miSim/initializeFromInits.m

@@ -1,87 +0,0 @@
-function obj = initializeFromInits(obj, initsPath)
-% INITIALIZEFROMINITS  Initialize miSim from a saved simInits matfile.
-%
-% Loads all simulation parameters and initial agent states written by
-% writeInits(), reconstructs domain, objective, agents, and obstacles, then
-% calls the standard obj.initialize() method.  Plots and video are disabled.
-%
-% Usage:
-%   sim = sim.initializeFromInits('sandbox/2025_01_01_12_00_00_miSimInits.mat');
-
-arguments (Input)
-    obj       (1, 1) {mustBeA(obj, 'miSim')};
-    initsPath (1, 1) string;
-end
-arguments (Output)
-    obj (1, 1) {mustBeA(obj, 'miSim')};
-end
-
-inits = load(initsPath);
-
-% ---- Build domain ------------------------------------------------------------
-dom = rectangularPrism;
-dom = dom.initialize([inits.domainMin; inits.domainMax], REGION_TYPE.DOMAIN, "Domain");
-
-% ---- Build sensing objective -------------------------------------------------
-dom.objective = sensingObjective;
-% reshape guards against MATLAB flattening the 1×2×2 singleton dimension on load
-objSigma = reshape(inits.objectiveSigma, [1 2 2]);
-objFcn = objectiveFunctionWrapper(inits.objectivePos, objSigma);
-dom.objective = dom.objective.initialize(objFcn, dom, ...
-    inits.discretizationStep, inits.protectedRange, inits.sensorPerformanceMinimum, ...
-    inits.objectivePos, objSigma);
-
-% ---- Build agents ------------------------------------------------------------
-numAgents = inits.numAgents;
-agentList = cell(numAgents, 1);
-for ii = 1:numAgents
-    pos = inits.pos(ii, :);
-
-    sensor = sigmoidSensor;
-    sensor = sensor.initialize(inits.alphaDist(ii), inits.betaDist(ii), ...
-                               inits.alphaTilt(ii), inits.betaTilt(ii));
-
-    geom = spherical;
-    geom = geom.initialize(pos, inits.collisionRadius(ii), REGION_TYPE.COLLISION, ...
-                           sprintf("UAV %d Collision", ii));
-    ag = agent;
-    ag = ag.initialize(pos, geom, sensor, inits.comRange(ii), inits.maxIter, ...
-                       inits.initialStepSize(ii), sprintf("UAV %d", ii));
-    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

@miSim/miSim.m

@@ -54,6 +54,7 @@ classdef miSim
         partitionGraphIndex = 1;
 
         % CBF plotting
+        h; % h function values
         hf; % h function plotting figure
         caPlot; % objects for collision avoidance h function plot
         obsPlot; % objects for obstacle h function plot
@@ -69,10 +70,8 @@ classdef miSim
             obj.obstacles = {rectangularPrism};
             obj.agents = {agent};
         end
-        [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology);
+        [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo);
         [obj] = initializeFromCsv(obj, csvPath);
-        [obj] = initializeFromInits(obj, initsPath);
-        [obj] = plotFromSimHist(obj, initsPath, histPath);
         [obj] = run(obj);
         [obj] = lesserNeighbor(obj);
         [obj] = constrainMotion(obj);

@miSim/plotFromSimHist.m

@@ -1,93 +0,0 @@
-function obj = plotFromSimHist(obj, initsPath, histPath)
-% PLOTFROMSIMHIST  Reconstruct all three miSim plots from saved matfiles.
-%
-% Loads the simInits matfile to rebuild domain/obstacle/objective/agent
-% geometry, then loads the simHist matfile to restore the full time-history
-% arrays.  Produces the same three figures that a live run would generate:
-%   1. Sensor performance vs. time  (obj.fPerf)
-%   2. Barrier function values vs. time  (obj.hf)
-%   3. 3-D spatial figure with domain, obstacles, objective, agent trails,
-%      and final-timestep communications topology  (obj.f)
-%
-% Usage:
-%   sim = miSim;
-%   sim = sim.plotFromSimHist( ...
-%       'sandbox/2025_01_01_12_00_00_miSimHist.mat', ...
-%       'sandbox/2025_01_01_12_00_00_miSimInits.mat');
-
-arguments (Input)
-    obj       (1, 1) {mustBeA(obj, 'miSim')};
-    initsPath (1, 1) string;
-    histPath  (1, 1) string;
-end
-arguments (Output)
-    obj (1, 1) {mustBeA(obj, 'miSim')};
-end
-
-% ---- Reconstruct geometry from inits (plots disabled) --------------------
-obj = obj.initializeFromInits(initsPath);
-nAgents = size(obj.agents, 1);
-
-% ---- Load history data ---------------------------------------------------
-data = load(histPath);
-out  = data.out;
-
-nHistTimesteps = size(out.barriers, 2);
-nPosTimesteps  = size(out.agent(1).pos, 1);
-
-% ---- Populate barrier history --------------------------------------------
-% out.barriers may be narrower than the pre-allocated obj.barriers if the
-% run was shorter than maxIter; fill what we have and leave the rest NaN.
-obj.barriers(:, 1:nHistTimesteps) = out.barriers;
-
-% ---- Populate position history and advance agents to final positions -----
-for ii = 1:nAgents
-    agentPos = out.agent(ii).pos;           % (nPosTimesteps × 3)
-    nPts = size(agentPos, 1);
-    obj.posHist(ii, 1:nPts, :) = reshape(agentPos, [1, nPts, 3]);
-    obj.agents{ii}.pos = agentPos(end, :);  % show final position in spatial plot
-end
-
-% ---- Set final constraint topology ---------------------------------------
-obj.constraintAdjacencyMatrix = out.constraintAdjacency(:, :, end);
-
-% ---- Recompute partitioning at final agent positions ---------------------
-obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
-
-% ---- Enable plotting and produce spatial + barrier figures ---------------
-obj.makePlots = true;
-obj = obj.plot();
-
-% ---- Performance figure (built directly — live machinery is incremental) -
-nPerfTimesteps = numel(out.perf);
-times = (0:nPerfTimesteps - 1) * obj.timestep;
-normFactor = 1 / max(out.perf);
-
-obj.fPerf = figure;
-ax = axes(obj.fPerf);
-hold(ax, "on");
-title(ax,  "Sensor Performance");
-xlabel(ax, "Time (s)");
-ylabel(ax, "Sensor Performance");
-grid(ax, "on");
-
-legendStrings = strings(nAgents + 1, 1);
-legendStrings(1) = "Total";
-plot(ax, times, out.perf * normFactor, "LineWidth", 1.5);
-for ii = 1:nAgents
-    agentPerf  = out.agent(ii).perf;
-    agentTimes = times(1:numel(agentPerf));
-    plot(ax, agentTimes, agentPerf * normFactor);
-    if isfield(out.agent(ii), 'label')
-        legendStrings(ii + 1) = string(out.agent(ii).label);
-    else
-        legendStrings(ii + 1) = sprintf("Agent %d", ii);
-    end
-end
-legend(ax, legendStrings, "Location", "northwest");
-hold(ax, "off");
-
-% Bring spatial figure to the front
-figure(obj.f);
-
-end

@miSim/plotH.m

@@ -6,10 +6,6 @@ function obj = plotH(obj)
         obj (1, 1) {mustBeA(obj, "miSim")};
     end
 
-    nCA  = size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2;
-    nObs = size(obj.agents, 1) * size(obj.obstacles, 1);
-    nDom = size(obj.agents, 1) * 6;
-
     obj.hf = figure;
     tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
 
@@ -19,7 +15,7 @@ function obj = plotH(obj)
     xlabel(obj.hf.Children(1).Children(1), "Time (s)");
     title(obj.hf.Children(1).Children(1), "Collision Avoidance");
     hold(obj.hf.Children(1).Children(1), "on");
-    obj.caPlot = plot(obj.barriers(1:nCA, :)');
+    obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)');
     legendStrings = [];
     for ii = 2:size(obj.agents, 1)
         for jj = 1:(ii - 1)
@@ -35,7 +31,7 @@ function obj = plotH(obj)
     xlabel(obj.hf.Children(1).Children(1), "Time (s)");
     title(obj.hf.Children(1).Children(1), "Obstacles");
     hold(obj.hf.Children(1).Children(1), "on");
-    obj.obsPlot = plot(obj.barriers((nCA + 1):(nCA + nObs), :)');
+    obj.obsPlot = plot(obj.h((1 + (size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)):(((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1)), :)');
     legendStrings = [];
     for ii = 1:size(obj.obstacles, 1)
         for jj = 1:size(obj.agents, 1)
@@ -51,13 +47,8 @@ function obj = plotH(obj)
     xlabel(obj.hf.Children(1).Children(1), "Time (s)");
     title(obj.hf.Children(1).Children(1), "Domain");
     hold(obj.hf.Children(1).Children(1), "on");
-    obj.domPlot = plot(obj.barriers((nCA + nObs + 1):(nCA + nObs + nDom), :)');
+    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)');
-    domLabels = ["X Min", "X Max", "Y Min", "Y Max", "Z Min", "Z Max"];
+    legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], "Location", "bestoutside");
-    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");
 
     nexttile(obj.hf.Children(1));

@miSim/run.m

@@ -11,10 +11,6 @@ function [obj] = run(obj)
         if obj.makeVideo
             v = obj.setupVideoWriter();
             v.open();
-            
-            % Write initialization state frame in to video
-            I = getframe(obj.f);
-            v.writeVideo(I);
         end
     end
 

@miSim/updatePlots.m

@@ -61,15 +61,13 @@ function [obj] = updatePlots(obj)
     end
 
     % Update h function plots
-    nCA  = size(obj.caPlot, 1);
+    for ii = 1:size(obj.caPlot, 1)
-    nObs = size(obj.obsPlot, 1);
+        obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
-    for ii = 1:nCA
-        obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
     end
-    for ii = 1:nObs
+    for ii = 1:size(obj.obsPlot, 1)
-        obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, obj.timestepIndex);
+        obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex);
     end
     for ii = 1:size(obj.domPlot, 1)
-        obj.domPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + nObs + ii, obj.timestepIndex);
+        obj.domPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1) + size(obj.obsPlot, 1), obj.timestepIndex);
     end
 end

@miSim/writeInits.m

@@ -5,35 +5,29 @@ function writeInits(obj)
     arguments (Output)
     end
 
-    % User-supplied obstacles only: initialize() appends a floor obstacle at
-    % the end when minAlt > 0, so exclude it here to avoid double-counting on
-    % reconstruction (initializeFromInits re-adds the floor via minAlt).
-    numInputObs = size(obj.obstacles, 1) - (obj.minAlt > 0);
-    userObstacles = obj.obstacles(1:numInputObs);
-
     % Collect agent parameters
     collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
     alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
     betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
     alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
-    betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
+    betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
     comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
     initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
     pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
-    obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, userObstacles, 'UniformOutput', false));
+    obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, obj.obstacles, 'UniformOutput', false));
-    obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, userObstacles, 'UniformOutput', false));
+    obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, obj.obstacles, 'UniformOutput', false));
+
 
     % Combine with simulation parameters
-    inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter + 1, "minAlt", obj.minAlt, ...
+    inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ...
                     "discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
                     "sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
-                    "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", numInputObs, ...
+                    "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
                     "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
-                    "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
+                    "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ...
                     "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
                     ... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
                     "pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
-                    "domainMin", obj.domain.minCorner, "domainMax", obj.domain.maxCorner, ...
                     "obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
                     "objectiveIntegral", sum(obj.domain.objective.values(:)));
 

@sensingObjective/initialize.m

@@ -47,5 +47,5 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
     end
     obj.objectiveSigma = objectiveSigma;
 
-    assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective");
+    assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
 end

@sensingObjective/initializeRandomMvnpdf.m

@@ -16,11 +16,11 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
     end
 
     % Set random distribution parameters
-    sig = reshape([2 + rand * 2, 1; 1, 2 + rand * 2], [1 2 2]);
+    sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
 
     % Set up random bivariate normal distribution function
     objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig);
 
     % Regular initialization
-    obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange, 1e-6, mu(1:2), sig);
+    obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange);
 end

aerpaw/client/uav_runner.py

@@ -164,7 +164,7 @@ class UAVRunner(BasicRunner):
 
         # Retry connection up to 10 times (~30 seconds total)
         reader, writer = None, None
-        for attempt in range(100):
+        for attempt in range(10):
             try:
                 reader, writer = await asyncio.wait_for(
                     asyncio.open_connection(self.server_ip, self.server_port),

aerpaw/config/client1.yaml

@@ -28,11 +28,11 @@ environments:
       port: 5000
 
   testbed:
-    # AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
+    # AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
     mavlink:
       ip: "192.168.32.26"
       port: 14550
-    # Controller runs on host machine (192.168.X.1, generally)
+    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
     controller:
-      ip: "192.168.112.1"
+      ip: "192.168.109.1"
       port: 5000

aerpaw/config/client2.yaml

@@ -28,11 +28,11 @@ environments:
       port: 5000
 
   testbed:
-    # AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
+    # AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
     mavlink:
       ip: "192.168.32.26"
       port: 14550
-    # Controller runs on host machine (192.168.X.1, generally)
+    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
     controller:
-      ip: "192.168.112.1"
+      ip: "192.168.109.1"
       port: 5000

aerpaw/config/scenario.csv

@@ -1,2 +1,2 @@
 timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
-1, 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, 150, 30.0, 0.1, 2.0, 1, 1, 1, "5.0, 5.0", "25.0, 25.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "80.0, 80.0, 80.0", "55.0, 55.0", "40, 25, 25, 40", 0.15, "15.0, 10.0, 40.0, 5.0, 10.0, 45.0", 1, "1.0, 25.0, 0.0", "30.0, 30.0, 50.0", 1, 2.0, 1

aerpaw/config/scenario_columns.csv

@@ -1,2 +0,0 @@
-timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
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aerpaw/config/scenario_lock.csv

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aerpaw/config/scenario_two_around_wall.csv

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aerpaw/config/scenario_walls.csv

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           </MF0>

aerpaw/controller.m

@@ -7,47 +7,34 @@ coder.extrinsic('disp', 'readScenarioCsv');
 
 % Maximum clients supported (one initial position per UAV)
 MAX_CLIENTS = 4;
-% Three waypoints per UAV: one axis-aligned move per dimension (taxicab flyout/flyback)
+MAX_TARGETS = MAX_CLIENTS;
-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)
 targets = zeros(MAX_TARGETS, 3);
 numWaypoints = int32(0);
 totalLoaded  = int32(0);  % pre-declare type for coder.ceval %#ok<NASGU>
 
-% Experiment start positions from scenario CSV (N x 3)
+% Load initial UAV positions from scenario CSV
-scenarioPositions = zeros(MAX_CLIENTS, 3);
-
-% Load experiment start positions from scenario CSV
 if coder.target('MATLAB')
     disp('Loading initial positions from scenario.csv (simulation)...');
     tmpSim = miSim;
     sc = tmpSim.readScenarioCsv('aerpaw/config/scenario.csv');
     flatPos = double(sc.initialPositions);  % 1×(3*N) flat vector
-    posMatrix = reshape(flatPos, 3, [])';   % N×3
+    posMatrix = reshape(flatPos, 3, [])';   % N×3, same layout as initializeFromCsv
     totalLoaded = int32(size(posMatrix, 1));
-    scenarioPositions(1:totalLoaded, :) = posMatrix;
-    % MATLAB path: send directly to scenario positions in one waypoint
     targets(1:totalLoaded, :) = posMatrix;
     numWaypoints = int32(1);
     disp(['Loaded ', num2str(double(totalLoaded)), ' initial positions']);
 else
     coder.cinclude('controller_impl.h');
     filename = ['config/scenario.csv', char(0)];
-    % Load into targets temporarily; copy to scenarioPositions below
     totalLoaded = coder.ceval('loadInitialPositions', coder.ref(filename), ...
                 coder.ref(targets), int32(MAX_TARGETS));
-    scenarioPositions(1:totalLoaded, :) = targets(1:totalLoaded, :);
+    numWaypoints = totalLoaded / int32(numClients);
-    numWaypoints = int32(3);
 end
 
 % Load guidance scenario from CSV (parameters for guidance_step)
-NUM_SCENARIO_PARAMS = 48;
+NUM_SCENARIO_PARAMS = 45;
 MAX_OBSTACLES_CTRL  = int32(8);
 scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
 obstacleMin    = zeros(MAX_OBSTACLES_CTRL, 3);
@@ -81,46 +68,6 @@ for i = 1:numClients
     end
 end
 
-% Query takeoff-pad GPS positions before sending any waypoints.
-% These are also the flyback targets so each UAV lands where it took off.
-initialPositions = zeros(MAX_CLIENTS, 3);
-if ~coder.target('MATLAB')
-    coder.ceval('sendRequestPositions', int32(numClients));
-    coder.ceval('recvPositions', int32(numClients), coder.ref(initialPositions), int32(MAX_CLIENTS));
-else
-    % Simulation: treat scenario positions as the takeoff locations
-    initialPositions(1:totalLoaded, :) = scenarioPositions(1:totalLoaded, :);
-end
-
-% ---- 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
 for w = 1:numWaypoints
     % Send TARGET for waypoint w to each client
@@ -131,7 +78,7 @@ for w = 1:numWaypoints
         target = targets(targetIdx, :);
 
         if coder.target('MATLAB')
-            disp(['Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
+            disp([datestr(now, 'HH:MM:SS'), ' Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
                   num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]);
         else
             coder.ceval('sendTarget', int32(i), coder.ref(target));
@@ -156,13 +103,8 @@ for w = 1:numWaypoints
 end
 
 % ---- Phase 2: miSim guidance loop ----------------------------------------
-% Number of guidance steps comes from maxIter in scenario.csv (scenarioParams(2))
+% Guidance parameters (adjust here and recompile as needed)
-% so the controller and the agent step-decay schedule stay in sync.
+MAX_GUIDANCE_STEPS = int32(100); % number of guidance iterations
-if coder.target('MATLAB')
-    MAX_GUIDANCE_STEPS = int32(sc.maxIter);
-else
-    MAX_GUIDANCE_STEPS = int32(scenarioParams(2));
-end
 
 % Enter guidance mode on all clients
 if ~coder.target('MATLAB')
@@ -175,18 +117,14 @@ if ~coder.target('MATLAB')
     coder.ceval('sendRequestPositions', int32(numClients));
     coder.ceval('recvPositions', int32(numClients), coder.ref(positions), int32(MAX_CLIENTS));
 else
-    % Simulation: seed positions from scenario positions so agents don't start at origin
+    % Simulation: seed positions from CSV waypoints so agents don't start at origin
-    positions(1:totalLoaded, :) = scenarioPositions(1:totalLoaded, :);
+    positions(1:totalLoaded, :) = targets(1:totalLoaded, :);
 end
 guidance_step(positions(1:numClients, :), true, ...
               scenarioParams, obstacleMin, obstacleMax, numObstacles);
 
 % Main guidance loop (event-triggered)
 for step = 1:MAX_GUIDANCE_STEPS
-    if ~coder.target('MATLAB')
-        coder.ceval('setGuidanceStep', int32(step), int32(MAX_GUIDANCE_STEPS));
-    end
-
     % Run one guidance step: feed current GPS positions in, get targets out
     nextPositions = guidance_step(positions(1:numClients, :), false, ...
                                   scenarioParams, obstacleMin, obstacleMax, numObstacles);
@@ -197,7 +135,7 @@ for step = 1:MAX_GUIDANCE_STEPS
         if ~coder.target('MATLAB')
             coder.ceval('sendTarget', int32(i), coder.ref(target));
         else
-            disp(['[step ', num2str(step), '] target UAV ', num2str(i), ': ', num2str(target)]);
+            disp([datestr(now, 'HH:MM:SS'), ' [guidance] target UAV ', num2str(i), ': ', num2str(target)]);
         end
     end
 
@@ -226,51 +164,6 @@ if ~coder.target('MATLAB')
     % last guidance navigation and is back in sequential (ACK/READY) mode.
     coder.ceval('waitForAllMessageType', int32(numClients), ...
                 int32(MESSAGE_TYPE.ACK));
-    % Reset step counter so post-guidance logging carries no step prefix.
-    coder.ceval('setGuidanceStep', int32(0), int32(MAX_GUIDANCE_STEPS));
-end
-% --------------------------------------------------------------------------
-
-% ---- 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
 % --------------------------------------------------------------------------
 

aerpaw/guidance_step.m

@@ -29,9 +29,6 @@ function nextPositions = guidance_step(currentPositions, isInit, ...
 %                                               39-40  objectivePos
 %                                               41-44  objectiveVar (2x2, col-major)
 %                                               45     sensorPerformanceMinimum
-%                                               46     useDoubleIntegrator
-%                                               47     dampingCoeff
-%                                               48     useFixedTopology
 %   obstacleMin       (MAX_OBSTACLES × 3) double  column-major obstacle corners (compiled path)
 %   obstacleMax       (MAX_OBSTACLES × 3) double
 %   numObstacles      (1,1) int32                 actual obstacle count
@@ -97,9 +94,6 @@ if isInit
         OBJECTIVE_GROUND_POS        = scenarioParams(39:40);
         OBJECTIVE_VAR               = reshape(scenarioParams(41:44), 2, 2);
         SENSOR_PERFORMANCE_MINIMUM  = scenarioParams(45);
-        USE_DOUBLE_INTEGRATOR       = logical(scenarioParams(46));
-        DAMPING_COEFF               = scenarioParams(47);
-        USE_FIXED_TOPOLOGY          = logical(scenarioParams(48));
 
         % --- Build domain geometry ---
         dom = rectangularPrism;
@@ -152,8 +146,7 @@ if isInit
         % --- Initialise simulation (plots and video disabled) ---
         sim = miSim;
         sim = sim.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
-                             MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
+                             MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
-                             USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
     end
 
     % On the init call return current positions unchanged
@@ -183,9 +176,7 @@ else
     sim.timestepIndex = sim.timestepIndex + 1;
 
     % 3. Update communications topology (Lesser Neighbour Assignment)
-    if ~sim.useFixedTopology
     sim = sim.lesserNeighbor();
-    end
 
     % 4. Compute Voronoi partitioning
     sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
@@ -193,8 +184,7 @@ else
     % 5. Unconstrained gradient-ascent step for each agent
     for ii = 1:size(sim.agents, 1)
         sim.agents{ii} = sim.agents{ii}.run(sim.domain, sim.partitioning, ...
-                                             sim.timestepIndex, ii, sim.agents, ...
+                                             sim.timestepIndex, ii, sim.agents);
-                                             sim.useDoubleIntegrator, sim.dampingCoeff, sim.timestep);
     end
 
     % 6. Apply CBF safety filter (collision / comms / domain constraints via QP)

aerpaw/impl/controller_impl.cpp

@@ -16,44 +16,6 @@
 
 static int serverSocket = -1;
 static std::vector<int> clientSockets;
-static int guidanceStep = 0;
-static int guidanceTotalSteps = 0;
-static struct timespec lastStepTime = {0, 0};
-
-// During guidance returns "(%d/%d) "; outside guidance returns "HH:MM:SS ".
-static std::string logPrefix() {
-    if (guidanceStep > 0) {
-        char buf[32];
-        snprintf(buf, sizeof(buf), "(%d/%d) ", guidanceStep, guidanceTotalSteps);
-        return std::string(buf);
-    }
-    time_t now = time(nullptr);
-    struct tm* lt = localtime(&now);
-    char ts[16];
-    strftime(ts, sizeof(ts), "%H:%M:%S", lt);
-    return std::string(ts) + " ";
-}
-
-void setGuidanceStep(int step, int totalSteps) {
-    struct timespec now;
-    clock_gettime(CLOCK_MONOTONIC, &now);
-
-    // From step 2 onward, elapsed = setGuidanceStep(N-1) → setGuidanceStep(N),
-    // which spans the full prior iteration: guidance computation + target send
-    // + flight + position request/receive.
-    if (step > 1 && lastStepTime.tv_sec != 0) {
-        double elapsed = (now.tv_sec - lastStepTime.tv_sec)
-                       + (now.tv_nsec - lastStepTime.tv_nsec) * 1e-9;
-        guidanceStep = step;
-        guidanceTotalSteps = totalSteps;
-        std::cout << logPrefix() << "Iteration duration: " << elapsed << " s\n";
-    } else {
-        guidanceStep = step;
-        guidanceTotalSteps = totalSteps;
-    }
-
-    lastStepTime = now;
-}
 
 void initSockets() {}
 void cleanupSockets() {}
@@ -224,10 +186,7 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
 //   35-37: domainMax  (east, north, up)
 //   38-39: objectivePos (east, north)
 //   40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
-//   44   : sensorPerformanceMinimum  (CSV column 18)
+//   44   : sensorPerformanceMinimum
-//   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.
 int loadScenario(const char* filename, double* params) {
     char line[4096];
@@ -239,8 +198,8 @@ int loadScenario(const char* filename, double* params) {
 
     char* fields[32];
     int nf = splitCSVRow(copy, fields, 32);
-    if (nf < 26) {
+    if (nf < 19) {
-        fprintf(stderr, "loadScenario: expected >=26 columns, got %d\n", nf);
+        fprintf(stderr, "loadScenario: expected >=19 columns, got %d\n", nf);
         return 0;
     }
 
@@ -331,24 +290,6 @@ int loadScenario(const char* filename, double* params) {
         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",
            params[32], params[33], params[34], params[35], params[36], params[37]);
     return 1;
@@ -489,22 +430,18 @@ static const char* messageTypeName(uint8_t msgType) {
     }
 }
 
-// Send a single-byte message type to a client (no logging)
+// Send a single-byte message type to a client
-static int sendMessageTypeRaw(int clientId, int msgType) {
+int sendMessageType(int clientId, int msgType) {
     if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0;
+
     uint8_t msg = (uint8_t)msgType;
     ssize_t sent = send(clientSockets[clientId - 1], &msg, 1, 0);
     if (sent != 1) {
         std::cerr << "Send failed for client " << clientId << "\n";
         return 0;
     }
-    return 1;
-}
 
-// Send a single-byte message type to a client
+    std::cout << "Sent " << messageTypeName(msg) << " to client " << clientId << "\n";
-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;
 }
 
@@ -523,7 +460,13 @@ int sendTarget(int clientId, const double* coords) {
         return 0;
     }
 
-    std::cout << logPrefix() << "Sent TARGET to client " << clientId << ": "
+    // Timestamp
+    time_t now = time(nullptr);
+    struct tm* lt = localtime(&now);
+    char ts[16];
+    strftime(ts, sizeof(ts), "%H:%M:%S", lt);
+
+    std::cout << ts << " Sent TARGET to client " << clientId << ": "
               << coords[0] << "," << coords[1] << "," << coords[2] << "\n";
     return 1;
 }
@@ -571,36 +514,31 @@ int waitForAllMessageType(int numClients, int expectedType) {
                     return 0;
                 }
 
+                std::cout << "Received " << messageTypeName(msgType) << " from client " << (i + 1) << "\n";
+
                 if (msgType == expected) {
                     completed[i] = true;
                     completedCount++;
-                } else {
-                    std::cerr << logPrefix() << "Unexpected " << messageTypeName(msgType)
-                              << " from client " << (i + 1)
-                              << " (expected " << messageTypeName(expected) << ")\n";
                 }
             }
         }
     }
 
-    std::cout << logPrefix() << "Received " << messageTypeName(expected) << " from all clients\n";
     return 1;
 }
 
 // Broadcast GUIDANCE_TOGGLE to all clients
 void sendGuidanceToggle(int numClients) {
     for (int i = 1; i <= numClients; i++) {
-        sendMessageTypeRaw(i, 6);  // GUIDANCE_TOGGLE = 6
+        sendMessageType(i, 6);  // GUIDANCE_TOGGLE = 6
     }
-    std::cout << logPrefix() << "Sent GUIDANCE_TOGGLE to clients\n";
 }
 
 // Send REQUEST_POSITION to all clients
 int sendRequestPositions(int numClients) {
     for (int i = 1; i <= numClients; i++) {
-        if (!sendMessageTypeRaw(i, 7)) return 0;  // REQUEST_POSITION = 7
+        if (!sendMessageType(i, 7)) return 0;  // REQUEST_POSITION = 7
     }
-    std::cout << logPrefix() << "Sent REQUEST_POSITION to clients\n";
     return 1;
 }
 
@@ -635,7 +573,7 @@ int recvPositions(int numClients, double* positions, int maxClients) {
         positions[i + 1 * maxClients] = coords[1];  // north (y)
         positions[i + 2 * maxClients] = coords[2];  // up    (z)
 
-        std::cout << logPrefix() << "Position from client " << (i + 1) << ": "
+        std::cout << "Position from client " << (i + 1) << ": "
                   << coords[0] << "," << coords[1] << "," << coords[2] << "\n";
     }
     return 1;

aerpaw/impl/controller_impl.h

@@ -30,10 +30,7 @@ int loadTargets(const char* filename, double* targets, int maxClients);
 //   38-39 objectivePos
 //   40-43 objectiveVar (2x2 col-major)
 //   44    sensorPerformanceMinimum
-//   45    useDoubleIntegrator  (0=single-integrator, 1=double-integrator)
+#define NUM_SCENARIO_PARAMS 45
-//   46    dampingCoeff
-//   47    useFixedTopology     (0=dynamic lesser-neighbor, 1=fixed)
-#define NUM_SCENARIO_PARAMS 48
 #define MAX_CLIENTS_PER_PARAM 4
 // Maximum number of obstacles (upper bound for pre-allocated arrays).
 #define MAX_OBSTACLES 8
@@ -62,7 +59,6 @@ int sendTarget(int clientId, const double* coords);
 int waitForAllMessageType(int numClients, int expectedType);
 
 // Guidance loop operations
-void setGuidanceStep(int step, int totalSteps);  // call at the top of each guidance iteration
 void sendGuidanceToggle(int numClients);
 int  sendRequestPositions(int numClients);
 int  recvPositions(int numClients, double* positions, int maxClients); // column-major maxClients x 3

aerpaw/radio/updateScripts.sh

@@ -13,4 +13,3 @@ cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
 
 echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
 echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"
-echo "REMEMBER! Manually copy startVehicle_controller.sh to ~/Profiles/ProfileScripts/Vehicle/startVehicle.sh on the fixed node"

aerpaw/results/plotGpsLogs.m

@@ -1,8 +1,7 @@
-function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
+function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
     arguments (Input)
         logDirs (1, 1) string;
         seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
-        plotWholeFlight (1, 1) logical = false;
     end
     arguments (Output)
         f (1, 1) matlab.ui.Figure;
@@ -29,7 +28,6 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
     logDirs = dir(logDirs);
     logDirs = logDirs(3:end);
     logDirs = logDirs([logDirs.isdir] == 1);
-    logDirs = logDirs(~startsWith({logDirs.name}, "controller_"));
 
     G = cell(size(logDirs));
     for ii = 1:size(logDirs, 1)
@@ -50,10 +48,8 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
         stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
     
         % % Plot whole flight, including setup/cleanup
-        if plotWholeFlight
+        % startIdx = 1;
-            startIdx = 1;
+        % stopIdx = length(verticalSpeed);
-            stopIdx = length(verticalSpeed);
-        end
 
         % Convert LLA trajectory data to ENU for external analysis
         % NaN out entries outside the algorithm flight range so they don't plot
@@ -62,27 +58,6 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
         enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
         G{ii} = [G{ii}, enu];
     
-        % Do crude comparison of pairwise distances between this UAV and
-        % all previous UAVs
-        for jj = 1:(ii - 1)
-            Ai = G{ii}(:, [1, end-2:end]);
-            Aj = G{jj}(:, [1, end-2:end]);
-
-            % Trim data to match sizes
-            idx = min([size(Ai, 1), size(Aj, 1)]);
-            Ai = Ai(1:idx, :); Aj = Aj(1:idx, :);
-
-            pos_i = [Ai.East, Ai.North, Ai.Up];
-            pos_j = [Aj.East, Aj.North, Aj.Up];
-            d = vecnorm(pos_i - pos_j, 2, 2);
-            d = d(~isnan(d));
-
-            fprintf("Minimum distance between agents %d and %d is %2.3f\n", ii, jj, min(d));
-            if min(d) < 6
-                warning("Minimum distance between agents %d and %d of %2.3f is questionable for AERPAW", ii, jj, min(d));
-            end
-        end
-    
         % Plot recorded trajectory over specified range of indices
         geoplot3(gf, G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx) + seaToGroundLevel, c(mod(ii, length(c))), 'LineWidth', 2, "MarkerSize", 5);
     end

aerpaw/results/readControllerLogs.m

@@ -1,32 +0,0 @@
-function T2 = readControllerLogs(filepath)
-    arguments (Input)
-        filepath (1, 1) string;
-    end
-    arguments (Output)
-        T2 table;
-    end
-    assert(isfile(filepath), "File not found at %s", filepath);
-
-    T = readtable(filepath, 'VariableNamingRule', 'preserve');
-    s = split(T.(T.Properties.VariableNames{1}), ']');
-    s2 = strip(s(startsWith(s(:, 2), " ("), 1), 'left', '[');
-    d = datetime(s2, "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS")';
-    it = s(startsWith(s(:, 2), " ("), 2);
-    it = str2double(strip(strip(it, 'left'), 'left', '('));
-    T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", T.Var7));
-    T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = [];
-    msg = T.(T.Properties.VariableNames{2});
-    msg = msg(startsWith(s(:, 2), " ("), :);
-    s3 = split(msg, ') ');
-    s3 = s3(:, 2);
-    msg = append(s3, T.Var3(startsWith(s(:, 2), " (")));
-    T2 = table(it, d', msg, 'VariableNames', ["iteration", "timestamp", "message"]);
-    % T.Var1 = datetime(strip(strip(append(T.Var1, " ", T.Var2), 'left', '['), 'right', ']'), "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS");
-    % T.Var2 = [];
-    % T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", string(T.Var7), " ", T.Var8, " ", T.Var9));
-    % T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = []; T.Var8 = []; T.Var9 = [];
-    % T.Properties.VariableNames{1} = 'timestamp';
-    % T.Properties.VariableNames{2} = 'message';
-
-    % T(ismissing(T.message), :) = [];
-end

aerpaw/results/readRadioLogs.m

@@ -2,6 +2,7 @@ function R = readRadioLogs(logPath)
     arguments (Input)
         logPath (1, 1) string {isfolder(logPath)};
     end
+
     arguments (Output)
         R (:, 8) table;
     end
@@ -30,26 +31,14 @@ function R = readRadioLogs(logPath)
         end
 
         fid = fopen(filepath, 'r');
-        % Skip header lines: some files have 2 tail-error lines + 1 column
+        % Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value)
-        % header ("tx_uav_id,value"), others start with data immediately.
+        for k = 1:3
-        % Read until a line that looks like a data record, then rewind to it.
+            fgetl(fid);
-        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
         data = textscan(fid, '[%26c] %d,%f');
         fclose(fid);
 
-        ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
+        ts = datetime(data{1}, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
         txId = int32(data{2});
         val = data{3};
 

aerpaw/results/resultsAnalysis.m

@@ -1,30 +1,9 @@
 %% Plot AERPAW logs (trajectory, radio)
 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)
 seaToGroundLevel = 110; % measured approximately from USGS national map viewer
-plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
+[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
-[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
 
 % Plot radio statistics
 [fRadio, R] = plotRadioLogs(resultsPath);
@@ -42,7 +21,7 @@ makeVideo = true;
 % Define scenario according to CSV specification
 domain = rectangularPrism;
 domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
-domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [1, 2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
+domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
 
 agents = cell(size(params.initialPositions, 2) / 3, 1);
 for ii = 1:size(agents, 1)

plots_1_2.m

@@ -0,0 +1,174 @@
+clear;
+
+%% Load data
+dataPath = fullfile('.', 'sandbox', 'plot1');
+dataFiles = dir(dataPath);
+dataFiles = dataFiles(~startsWith({dataFiles.name}, '.'));
+simInits = dataFiles(endsWith({dataFiles.name}, 'miSimInits.mat'));
+simHists = dataFiles(endsWith({dataFiles.name}, 'miSimHist.mat'));
+assert(length(simHists) == length(simInits), "input data availability mismatch");
+
+%% Aggregate run data
+nRuns = length(simHists);
+Cfinal = NaN(nRuns, 1);
+nAgents = NaN(nRuns, 1);
+doubleIntegrator = NaN(nRuns, 1);
+numObjective = NaN(nRuns, 1);
+commsRadius = NaN(nRuns, 1);
+collisionRadius = NaN(nRuns, 1);
+maxAgents = 6;
+alphaDist = NaN(maxAgents, nRuns);
+positions = cell(maxAgents, nRuns);
+adjacency = cell(nRuns, 1);
+
+for ii = 1:nRuns
+    initName = strrep(simInits(ii).name, "_miSimInits.mat", "");
+    histName = strrep(simHists(ii).name, "_miSimHist.mat", "");
+    assert(initName == histName);
+
+    init = load(fullfile(simInits(ii).folder, simInits(ii).name));
+    hist = load(fullfile(simHists(ii).folder, simHists(ii).name));
+
+    Cfinal(ii) = hist.out.perf(end) / init.objectiveIntegral;
+    nAgents(ii) = init.numAgents;
+    doubleIntegrator(ii) = init.useDoubleIntegrator;
+    numObjective(ii) = size(init.objectivePos, 1);
+    commsRadius(ii) = unique(init.comRange);
+    collisionRadius(ii) = unique(init.collisionRadius);
+
+    adjacency{ii} = hist.out.constraintAdjacency(:, :, 1);
+    for jj = 1:nAgents(ii)
+        alphaDist(jj, ii) = hist.out.agent(jj).sensor.alphaDist;
+        positions{jj, ii} = hist.out.agent(jj).pos;
+        assert(hist.out.agent(jj).commsRadius == commsRadius(ii));
+        assert(hist.out.agent(jj).collisionRadius == collisionRadius(ii));
+    end
+end
+
+commsRadius = unique(commsRadius); assert(isscalar(commsRadius));
+collisionRadius = unique(collisionRadius); assert(isscalar(collisionRadius));
+sensorTypes = flip(unique(alphaDist(1, :)));
+nValues = sort(unique(nAgents));
+nGroups = length(nValues);
+
+%% Build config labels
+baseConfig = strings(nRuns, 1);
+for ii = 1:nRuns
+    s = "";
+    if numObjective(ii) == 1
+        s = s + "A";
+    elseif numObjective(ii) == 2
+        s = s + "B";
+    end
+    if alphaDist(1, ii) == sensorTypes(1)
+        s = s + "_I";
+    elseif alphaDist(1, ii) == sensorTypes(2)
+        s = s + "_II";
+    end
+    if ~doubleIntegrator(ii)
+        s = s + "_alpha";
+    else
+        s = s + "_beta";
+    end
+    baseConfig(ii) = s;
+end
+configOrder = unique(baseConfig(nAgents == nValues(1)), 'stable');
+nConfigs = length(configOrder);
+configLabels = ["$AI\alpha$"; "$AI\beta$"; "$AII\alpha$"; "$BI\beta$"];
+
+%% Plot 1: Final normalized coverage
+close all;
+f1 = figure;
+x1 = axes;
+
+C_mean = NaN(nGroups, nConfigs);
+C_var = NaN(nGroups, nConfigs);
+for ii = 1:nGroups
+    for jj = 1:nConfigs
+        mask = (nAgents == nValues(ii)) & (baseConfig == configOrder(jj));
+        C_mean(ii, jj) = mean(Cfinal(mask));
+        C_var(ii, jj) = var(Cfinal(mask));
+    end
+end
+
+bar(x1, C_mean);
+set(x1, 'XTickLabel', string(nValues));
+xlabel(x1, "Number of agents");
+ylabel(x1, "Final coverage (normalized)");
+title(x1, "Final performance of parameterizations");
+legend(x1, configLabels, "Interpreter", "latex", "Location", "northwest");
+grid(x1, "on");
+ylim(x1, [0, 1/2]);
+
+savefig(f1, "plot1.fig");
+exportgraphics(f1, "plot1.png");
+
+%% Plot 2: Pairwise agent distances
+f2 = figure;
+x2 = axes;
+
+% Compute pairwise distances only for connected agents (static topology)
+maxPairs = nchoosek(maxAgents, 2);
+pairDist = cell(maxPairs, nRuns);
+for ii = 1:nRuns
+    A = adjacency{ii};
+    pp = 0;
+    for jj = 1:nAgents(ii)-1
+        for kk = jj+1:nAgents(ii)
+            pp = pp + 1;
+            if A(jj, kk)
+                pairDist{pp, ii} = vecnorm(positions{jj, ii} - positions{kk, ii}, 2, 2);
+            end
+        end
+    end
+end
+
+% Per-run statistics across all pairs and timesteps
+meanPairDist = NaN(nRuns, 1);
+minPairDist = NaN(nRuns, 1);
+maxPairDist = NaN(nRuns, 1);
+for ii = 1:nRuns
+    nPairs = nchoosek(nAgents(ii), 2);
+    D = vertcat(pairDist{1:nPairs, ii});
+    meanPairDist(ii) = mean(D, "omitmissing");
+    minPairDist(ii) = min(D);
+    maxPairDist(ii) = max(D);
+end
+
+% Aggregate across trials per (n, config) group
+meanD = NaN(nGroups, nConfigs);
+minD = NaN(nGroups, nConfigs);
+maxD = NaN(nGroups, nConfigs);
+for ii = 1:nGroups
+    for jj = 1:nConfigs
+        mask = (nAgents == nValues(ii)) & (baseConfig == configOrder(jj));
+        meanD(ii, jj) = mean(meanPairDist(mask));
+        minD(ii, jj) = min(minPairDist(mask));
+        maxD(ii, jj) = max(maxPairDist(mask));
+    end
+end
+
+% Plot whiskers (min to max) with mean markers
+barWidth = 0.8;
+groupWidth = barWidth / nConfigs;
+hold(x2, 'on');
+for jj = 1:nConfigs
+    xPos = (1:nGroups) + (jj - (nConfigs + 1) / 2) * groupWidth;
+    errorbar(x2, xPos, meanD(:, jj), meanD(:, jj) - minD(:, jj), maxD(:, jj) - meanD(:, jj), ...
+        'o', 'LineWidth', 1.5, 'MarkerSize', 6, 'CapSize', 10);
+end
+hold(x2, 'off');
+set(x2, 'XTick', 1:nGroups, 'XTickLabel', string(nValues));
+xlabel(x2, "Number of agents");
+ylabel(x2, "Pairwise distance");
+title(x2, "Pairwise Agent Distances (min/mean/max)");
+legend(x2, configLabels, "Interpreter", "latex");
+grid(x2, "on");
+yline(x2, collisionRadius, 'r--', "Label", "Collision Radius", ...
+    "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+yline(x2, commsRadius, 'r--', "Label", "Communications Radius", ...
+    "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+ylim(x2, [0, commsRadius + 5]);
+
+savefig(f2, "plot2.fig");
+exportgraphics(f2, "plot2.png");

plots_3_4.m

@@ -0,0 +1,120 @@
+clear;
+
+%% Load data
+dataPath = fullfile('.', 'sandbox', 'plot3');
+dataFiles = dir(dataPath);
+dataFiles = dataFiles(~startsWith({dataFiles.name}, '.'));
+simInits = dataFiles(endsWith({dataFiles.name}, 'miSimInits.mat'));
+simHists = dataFiles(endsWith({dataFiles.name}, 'miSimHist.mat'));
+assert(length(simHists) == length(simInits), "input data availability mismatch");
+assert(isscalar(simHists));
+
+init = load(fullfile(simInits(1).folder, simInits(1).name));
+hist = load(fullfile(simHists(1).folder, simHists(1).name));
+hist = hist.out;
+
+%% Plot 3: Per-agent and cumulative normalized performance
+assert(size(init.objectivePos, 1) == 1);
+assert(hist.useDoubleIntegrator);
+
+nAgents = length(hist.agent);
+agentLabels = "Agent " + string(1:nAgents)';
+
+f3 = figure;
+x3 = axes;
+hold(x3, 'on');
+plot(x3, hist.perf ./ init.objectiveIntegral, "LineWidth", 2);
+for ii = 1:nAgents
+    plot(x3, hist.agent(ii).perf ./ init.objectiveIntegral, "LineWidth", 2);
+end
+hold(x3, 'off');
+grid(x3, "on");
+ylabel(x3, "Performance (normalized)");
+xlabel(x3, "Timestep");
+legend(x3, ["Cumulative"; agentLabels], "Location", "northwest");
+title(x3, "$AII\beta$ Performance", "Interpreter", "latex");
+
+savefig(f3, "plot3.fig");
+exportgraphics(f3, "plot3.png");
+
+%% Plot 4: Pairwise distances and barrier functions
+commsRadius = hist.agent(1).commsRadius;
+collisionRadius = hist.agent(1).collisionRadius;
+nPairs = nchoosek(nAgents, 2);
+T = size(hist.agent(1).pos, 1);
+
+% Compute pairwise distances over time
+pairDistMat = NaN(T, nPairs);
+pairLabels = strings(nPairs, 1);
+pp = 0;
+for jj = 1:nAgents-1
+    for kk = jj+1:nAgents
+        pp = pp + 1;
+        pairDistMat(:, pp) = vecnorm(hist.agent(jj).pos - hist.agent(kk).pos, 2, 2);
+        pairLabels(pp) = sprintf("Agents %d-%d Distance", jj, kk);
+    end
+end
+
+f4 = figure;
+x4 = axes;
+
+% Left Y-axis: pairwise distances
+hold(x4, 'on');
+hLeft = gobjects(nPairs, 1);
+for pp = 1:nPairs
+    hLeft(pp) = plot(x4, pairDistMat(:, pp), 'LineWidth', 2);
+end
+yline(x4, collisionRadius, 'r--', "Label", "Collision Radius", ...
+    "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+yline(x4, commsRadius, 'r--', "Label", "Communications Radius", ...
+    "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+hold(x4, 'off');
+xlabel(x4, "Timestep");
+ylabel(x4, "Pairwise distance");
+title(x4, "$AII\beta$ Pairwise Agent Distances and Barrier Function Values", "Interpreter", "latex");
+grid(x4, "on");
+
+savefig(f4, "plot4_distanceOnly.fig");
+exportgraphics(f4, "plot4_distanceOnly.png");
+
+% Right Y-axis: barrier function values
+nObs = init.numObstacles;
+nAA = nchoosek(nAgents, 2);
+nAO = nAgents * nObs;
+nAD = nAgents * 6;
+nComms = size(hist.barriers, 1) - nAA - nAO - nAD;
+
+colStart = 1;
+comStart = colStart + nAA + nAO + nAD;
+
+pairColors = lines(nAA);
+
+yyaxis(x4, 'right');
+hold(x4, 'on');
+hRight = gobjects(nAA + nComms, 1);
+rightLabels = strings(nAA + nComms, 1);
+idx = 0;
+for pp = 1:nAA
+    idx = idx + 1;
+    hRight(idx) = plot(x4, hist.barriers(colStart + pp - 1, :), '--', ...
+        'LineWidth', 1.5, 'Color', pairColors(pp, :));
+    rightLabels(idx) = sprintf('h_{col} %d', pp);
+end
+for pp = 1:nComms
+    idx = idx + 1;
+    hRight(idx) = plot(x4, hist.barriers(comStart + pp - 1, :), '-.', ...
+        'LineWidth', 1.5, 'Color', pairColors(pp, :));
+    rightLabels(idx) = sprintf('h_{com} %d', pp);
+end
+hold(x4, 'off');
+ylabel(x4, "Barrier function $h$", "Interpreter", "latex");
+
+% Y-axis limits
+yyaxis(x4, 'left');  ylim(x4, [0, 25]);
+yyaxis(x4, 'right'); ylim(x4, [0, 275]);
+x4.YAxis(2).Color = 'k';
+
+legend([hLeft(:); hRight(:)], [pairLabels(:); rightLabels(:)], "Location", "eastoutside");
+
+savefig(f4, "plot4.fig");
+exportgraphics(f4, "plot4.png");

resources/project/6V6Vr7QAsqxEmRj-ezOm1ygcTak/bJiTrGQ5GQ9DMI6whRMInBQY2yQd.xml

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

resources/project/6V6Vr7QAsqxEmRj-ezOm1ygcTak/bJiTrGQ5GQ9DMI6whRMInBQY2yQp.xml

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

resources/project/71xh8lboMaPoa5Dmw3ABwzIozfw/bjgcAyD7dxJIgrUo3yHl5f1-iksd.xml

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

resources/project/71xh8lboMaPoa5Dmw3ABwzIozfw/bjgcAyD7dxJIgrUo3yHl5f1-iksp.xml

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

resources/project/AYz988O6MmLDfGQa1POLekzFkGo/YCy7McFB8-ln__QHYP5j7X7nQI8d.xml

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

resources/project/AYz988O6MmLDfGQa1POLekzFkGo/YCy7McFB8-ln__QHYP5j7X7nQI8p.xml

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

resources/project/FI0gxbH-PhwjE_riDQGHPyYMHks/q1TwgWjEDIn-a93hPi1WGodL3NYd.xml

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <Info>
     <Category UUID="FileClassCategory">
-        <Label UUID="design"/>
+        <Label UUID="test"/>
     </Category>
 </Info>

resources/project/FI0gxbH-PhwjE_riDQGHPyYMHks/q1TwgWjEDIn-a93hPi1WGodL3NYp.xml

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

resources/project/Hp7WImb16Wc_c7gK28oUydAFVts/EhSD3dO3mU2KP9IqbTVz7g60j5Ad.xml

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

resources/project/Hp7WImb16Wc_c7gK28oUydAFVts/EhSD3dO3mU2KP9IqbTVz7g60j5Ap.xml

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

resources/project/QVXvsR5cXQzGBi9QgRUFaflegRY/SltMFP7zr3UZsLPdRi9OyWAN7pMd.xml

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

resources/project/QVXvsR5cXQzGBi9QgRUFaflegRY/SltMFP7zr3UZsLPdRi9OyWAN7pMp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/_1CKOWXf9sLpzeC642i06VHUH0Qp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/abbdKJ8UvIXKWL0sR9NW0pEJSNIp.xml

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

resources/project/Vq0hyJJCG53DJ8wxA_8WUihyBpg/H9TIrKqi-fFOWfgKFbIj3tQLZ3Yd.xml

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

resources/project/Vq0hyJJCG53DJ8wxA_8WUihyBpg/H9TIrKqi-fFOWfgKFbIj3tQLZ3Yp.xml

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

resources/project/Xaysz7d0ZEEdz7yS61mKTAp17xo/GbYZ0TkPTXbbWS6cBc7HG5YmHQId.xml

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

resources/project/Xaysz7d0ZEEdz7yS61mKTAp17xo/GbYZ0TkPTXbbWS6cBc7HG5YmHQIp.xml

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

resources/project/cCclYJTOop6jkdZsItlf7iNuov4/boyWn-mt0RFdVNBj1mgEcGMQh_Ep.xml

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

resources/project/ls4G1ReemmlA4lw5Sxijq_iTPE0/YTBPi7yO4zYK5U1mxnqJDcdXNYkd.xml

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

resources/project/ls4G1ReemmlA4lw5Sxijq_iTPE0/YTBPi7yO4zYK5U1mxnqJDcdXNYkp.xml

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

resources/project/o8EfsliYZoi0Pg0hEr9bLYBd-k0/C05cVxQ9NvFXxKc5bQbtmN_GvSAd.xml

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

resources/project/o8EfsliYZoi0Pg0hEr9bLYBd-k0/C05cVxQ9NvFXxKc5bQbtmN_GvSAp.xml

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

resources/project/pjpApCZ_IyThRbNNVtyf0HS9lGA/OvzpqD8IaJL2rl4SaQSOPQ-QRMkd.xml

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

resources/project/pjpApCZ_IyThRbNNVtyf0HS9lGA/OvzpqD8IaJL2rl4SaQSOPQ-QRMkp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/6V6Vr7QAsqxEmRj-ezOm1ygcTakd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/6V6Vr7QAsqxEmRj-ezOm1ygcTakp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test4" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/71xh8lboMaPoa5Dmw3ABwzIozfwd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/71xh8lboMaPoa5Dmw3ABwzIozfwp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test13" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/AYz988O6MmLDfGQa1POLekzFkGod.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/AYz988O6MmLDfGQa1POLekzFkGop.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plot3" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Hp7WImb16Wc_c7gK28oUydAFVtsd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Hp7WImb16Wc_c7gK28oUydAFVtsp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="t1" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/QVXvsR5cXQzGBi9QgRUFaflegRYd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/QVXvsR5cXQzGBi9QgRUFaflegRYp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test14" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Vq0hyJJCG53DJ8wxA_8WUihyBpgd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Vq0hyJJCG53DJ8wxA_8WUihyBpgp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test11" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Xaysz7d0ZEEdz7yS61mKTAp17xod.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Xaysz7d0ZEEdz7yS61mKTAp17xop.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plot1_2" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/ls4G1ReemmlA4lw5Sxijq_iTPE0d.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/ls4G1ReemmlA4lw5Sxijq_iTPE0p.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test6" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/o8EfsliYZoi0Pg0hEr9bLYBd-k0d.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/o8EfsliYZoi0Pg0hEr9bLYBd-k0p.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plot1" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/pjpApCZ_IyThRbNNVtyf0HS9lGAd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/pjpApCZ_IyThRbNNVtyf0HS9lGAp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test3" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/soCFsvL91lhqvUw-h8HkHCtfsiwd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/soCFsvL91lhqvUw-h8HkHCtfsiwp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test10" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/yqgj8VLvTZ-pn09SsztajkpKW1Ed.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/yqgj8VLvTZ-pn09SsztajkpKW1Ep.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="test12" type="File"/>

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/zpVmgHK5gbVcPgNcOE2ip90e6Dwd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/zpVmgHK5gbVcPgNcOE2ip90e6Dwp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plot1_3" type="File"/>

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/FAIFc6EGkYrae07xGB2jWoFdM-0p.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plots_3_4.m" type="File"/>

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/cQhJ0S-hbiRJRVZSMGQe9M3c01Yp.xml

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Info location="plots_1_2.m" type="File"/>

resources/project/soCFsvL91lhqvUw-h8HkHCtfsiw/1fQ44ZBWSpGWUWzrR6iBNoEkvh4d.xml

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

resources/project/soCFsvL91lhqvUw-h8HkHCtfsiw/1fQ44ZBWSpGWUWzrR6iBNoEkvh4p.xml

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

resources/project/yqgj8VLvTZ-pn09SsztajkpKW1E/68s6SYUbIV2lonVX55ZsTcaPe_4d.xml

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

resources/project/yqgj8VLvTZ-pn09SsztajkpKW1E/68s6SYUbIV2lonVX55ZsTcaPe_4p.xml

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

resources/project/zpVmgHK5gbVcPgNcOE2ip90e6Dw/WwFoZBvO-jYGdGTuAqgFvzbHuysd.xml

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

resources/project/zpVmgHK5gbVcPgNcOE2ip90e6Dw/WwFoZBvO-jYGdGTuAqgFvzbHuysp.xml

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

test/parametricTestSuite.m

@@ -34,14 +34,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
 
             % Define scenario according to CSV specification
             tc.domain = tc.domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
-            if length(params.objectiveVar) > 4 && length(params.objectivePos) > 2
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), tc.domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
-                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);
             for ii = 1:size(agents, 1)
@@ -88,8 +81,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
             for ii = 1:size(params.timestep, 1)
                 % Set up square domain
                 tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
-                objectiveCenter = [.75 * l, 0.75 * l];
+                tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii));
-                tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(objectiveCenter), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii), objectiveCenter);
                 
                 % Initialize agents
                 agents = cell(params.numAgents(ii), 1);

test/results.m

@@ -0,0 +1,338 @@
+classdef results < matlab.unittest.TestCase
+    properties (Constant, Access = private)
+        seed = 1;
+        domainSize = [150, 150, 100]; % fixed domain size [X, Y, Z]
+    end
+
+    properties (Access = private)
+        % System under test
+        testClass = miSim;
+
+        %% Diagnostic Parameters
+        % No effect on simulation dynamics
+        makeVideo = false; % disable video writing for big performance increase
+        makePlots = false; % disable plotting for big performance increase (also disables video)
+        plotCommsGeometry = false; % disable plotting communications geometries
+
+        %% Scenario Reinitialization
+        % Number of extra reinitializations per test case (3 n-values x 4 configs = 12).
+        % Order: n3/A_1_alpha, n3/A_1_beta, n3/A_2_alpha, n3/B_1_beta,
+        %        n5/A_1_alpha, ..., n6/B_1_beta
+        % Set inspectScenarios = true to pause after init for manual review.
+        % At the keyboard prompt, type the number of reinits needed into
+        % the variable 'reinitCount', then 'dbcont' to continue.
+        inspectScenarios = false;
+        reinit = zeros(1, 12);
+
+        %% Fixed Test Parameters
+        useFixedTopology = true; % No lesser neighbor, fixed network instead
+        discretizationStep = 0.5;
+        protectedRange = 5;
+        collisionRadius = 5;
+        sensorPerformanceMinimum = 0.005;
+        comRange = 20;
+        maxIter = 400;
+        initialStepSize = 1;
+        % Each row: [minX minY minZ maxX maxY maxZ]
+        obstacleCorners = [results.domainSize(1)/2, results.domainSize(2)*5/8, 0, results.domainSize(1)*5/8, results.domainSize(2), 35;
+                           results.domainSize(1)/3, 0, 0, results.domainSize(1)/2, results.domainSize(2)*3/8, 40];
+        barrierGain = 1;
+        barrierExponent = 1;
+        timestep = 0.5;
+        dampingCoeff = 2;
+    end
+
+    properties (TestParameter)
+        %% Test Iterations
+        % Specific parameter combos to run iterations on
+        n = struct('n3', 3, 'n5', 5, 'n6', 6); % number of agents
+        config = results.makeConfigs();
+    end
+
+    properties (MethodSetupParameter)
+        trials = struct('r1', 1, 'r2', 2, 'r3', 3, 'r4', 4, 'r5', 5);
+    end
+
+    methods (TestMethodSetup)
+        function setSeed(tc, trials)
+            rng(tc.seed + trials);
+        end
+    end
+
+    methods (Static, Access = public)
+        function c = makeConfigs()
+            rng(results.seed);
+            abMin = 6; % alpha*beta >= 6 ensures membership(0) = tanh(3) >= 0.995
+            alphaDist = rand(1, 2) .* [75, 45];
+            betaDist = abMin ./ alphaDist + rand(1, 2) .* [1, 1/8] .* (20 - abMin ./ alphaDist);
+            alphaTilt = 10 + rand(1, 2) .* [20, 20];
+            betaTilt = abMin ./ alphaTilt + rand(1, 2) .* (50 - abMin ./ alphaTilt);
+            sensors = struct('alphaDist', num2cell(alphaDist), 'alphaTilt', num2cell(alphaTilt), 'betaDist', num2cell(betaDist), 'betaTilt', num2cell(betaTilt));
+            sensor1 = sigmoidSensor;
+            sensor2 = sigmoidSensor;
+            sensor1 = sensor1.initialize(sensors(1).alphaDist, sensors(1).betaDist, sensors(1).alphaTilt, sensors(1).betaTilt);
+            sensor2 = sensor2.initialize(sensors(2).alphaDist, sensors(2).betaDist, sensors(2).alphaTilt, sensors(2).betaTilt);
+            % sensor1.plotParameters;
+            % sensor2.plotParameters;
+            c = struct('A_1_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', false), ...
+                        'A_1_beta',  struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(1), 'doubleIntegrator', true), ...
+                        'A_2_alpha', struct('objectivePos', [3, 1] / 4 .* results.domainSize(1:2), 'sensor', sensors(2), 'doubleIntegrator', false), ...
+                        'B_1_beta',  struct('objectivePos', [[3, 1] / 4 .* results.domainSize(1:2); [3, 1] / 4 .* results.domainSize(1:2) + 25 .* [-1, 1] ./ sqrt(2)], 'sensor', sensors(1), 'doubleIntegrator', true));
+        end
+    end
+
+    methods (Test)
+        function plot1_runs(tc, n, config)
+            % if n == 5 && config.doubleIntegrator == true
+            %     tc.makePlots = true;
+            % else
+            %     tc.makePlots = false;
+            % end
+            % Compute test case index for reinit lookup
+            nKeys = fieldnames(tc.n);
+            configKeys = fieldnames(tc.config);
+            nIdx = find(cellfun(@(k) tc.n.(k) == n, nKeys));
+            configIdx = find(cellfun(@(k) isequal(tc.config.(k), config), configKeys));
+            testIdx = (nIdx - 1) * numel(configKeys) + configIdx;
+
+            % Determine number of reinitializations
+            reinitCount = tc.reinit(testIdx);
+
+            for reroll = 0:reinitCount
+
+            % Set up fixed-size domain
+            minAlt = tc.domainSize(3)/10 + rand * 1/10 * tc.domainSize(3);
+            % Place sensing objective(s) at fixed positions from config
+            objectiveMu = config.objectivePos;
+            numDist = size(objectiveMu, 1);
+            objectiveSigma = [];
+            for ii = 1:numDist
+                sig = [200, 140; 140, 280];
+                if ~mod(ii, 2)
+                    sig = rot90(sig,2);
+                end
+                sig = reshape(sig, [1, 2, 2]);
+                objectiveSigma = cat(1, objectiveSigma, sig);
+            end
+            tc.testClass.domain = tc.testClass.domain.initialize([zeros(1, 3); tc.domainSize], REGION_TYPE.DOMAIN, "Domain");
+            tc.testClass.domain.objective = tc.testClass.domain.objective.initialize(objectiveFunctionWrapper(objectiveMu, objectiveSigma), tc.testClass.domain, tc.discretizationStep, tc.protectedRange, tc.sensorPerformanceMinimum, objectiveMu, objectiveSigma);
+            
+            % Initialize agents
+            agents = cell(n, 1);
+            [agents{:}] = deal(agent);
+
+            % Initialize sensor model
+            sensorModel = sigmoidSensor;
+            sensorModel = sensorModel.initialize(config.sensor.alphaDist, config.sensor.betaDist, config.sensor.alphaTilt, config.sensor.betaTilt);
+
+            % Initialize fixed obstacles from corner coordinates
+            nObs = size(tc.obstacleCorners, 1);
+            obstacles = cell(nObs, 1);
+            for jj = 1:nObs
+                corners = [tc.obstacleCorners(jj, 1:3); tc.obstacleCorners(jj, 4:6)];
+                obstacles{jj} = rectangularPrism;
+                obstacles{jj} = obstacles{jj}.initialize(corners, REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", jj));
+            end
+
+            % Place agents in small-x, large-y quadrant (opposite objectives)
+            % with chain topology: each agent connected only to its neighbors
+            midXY = (tc.testClass.domain.minCorner(1:2) + tc.testClass.domain.maxCorner(1:2)) / 2;
+            quadrantSize = tc.testClass.domain.maxCorner(1:2) / 2;
+            margin = quadrantSize / 6;
+            agentBounds = [tc.testClass.domain.minCorner(1) + margin(1), ...
+                           midXY(2) + margin(2); ...
+                           midXY(1) - margin(1), ...
+                           tc.testClass.domain.maxCorner(2) - margin(2)];
+            % Find a fixed altitude where sensor performance passes at ALL
+            % corners of the placement bounds (worst-case XY)
+            corners = [agentBounds(1,1), agentBounds(1,2);
+                       agentBounds(2,1), agentBounds(1,2);
+                       agentBounds(1,1), agentBounds(2,2);
+                       agentBounds(2,1), agentBounds(2,2)];
+            agentAlt = tc.testClass.domain.maxCorner(3) - tc.collisionRadius;
+            while agentAlt > minAlt + 2 * tc.collisionRadius
+                worstPerf = inf;
+                for cc = 1:4
+                    p = sensorModel.sensorPerformance([corners(cc,:), agentAlt], [corners(cc,:), 0]);
+                    worstPerf = min(worstPerf, p);
+                end
+                if worstPerf >= tc.sensorPerformanceMinimum * 10
+                    break;
+                end
+                agentAlt = agentAlt - 1;
+            end
+            chainSpacingMin = 0.7 * tc.comRange;
+            chainSpacingMax = 0.9 * tc.comRange;
+            collisionGeometry = spherical;
+            for jj = 1:n
+                retry = true;
+                while retry
+                    retry = false;
+
+                    if jj == 1
+                        % First agent: random XY within bounds, fixed altitude
+                        agentPos = [agentBounds(1, :) + (agentBounds(2, :) - agentBounds(1, :)) .* rand(1, 2), agentAlt];
+                    else
+                        % Place at 0.7-0.9 * comRange in XY from previous agent, same altitude
+                        dir = randn(1, 2);
+                        dir = dir / norm(dir);
+                        r = chainSpacingMin + rand * (chainSpacingMax - chainSpacingMin);
+                        agentPos = [agents{jj-1}.pos(1:2) + r * dir, agentAlt];
+                    end
+
+                    % Check within placement bounds (XY only, Z is fixed)
+                    if any(agentPos(1:2) <= agentBounds(1, :)) || any(agentPos(1:2) >= agentBounds(2, :))
+                        retry = true;
+                        continue;
+                    end
+
+                    % Check sensor performance threshold; lower altitude if it fails
+                    if sensorModel.sensorPerformance(agentPos, [agentPos(1:2), 0]) < tc.sensorPerformanceMinimum * 10
+                        agentAlt = max(agentAlt - tc.collisionRadius, minAlt + 1.1 * tc.collisionRadius);
+                        agentPos(3) = agentAlt;
+                        % If we've hit the floor and still failing, widen XY search
+                        if agentAlt <= minAlt + 2 * tc.collisionRadius
+                            agentBounds = [tc.testClass.domain.minCorner(1) + tc.collisionRadius, ...
+                                           tc.testClass.domain.minCorner(2) + tc.collisionRadius; ...
+                                           tc.testClass.domain.maxCorner(1) - tc.collisionRadius, ...
+                                           tc.testClass.domain.maxCorner(2) - tc.collisionRadius];
+                        end
+                        retry = true;
+                        continue;
+                    end
+
+                    % Must be within comRange of previous agent (chain link)
+                    if jj > 1 && norm(agents{jj-1}.pos - agentPos) >= tc.comRange
+                        retry = true;
+                        continue;
+                    end
+
+                    % Must be BEYOND comRange of all non-adjacent agents (sparsity)
+                    % for kk = 1:(jj - 2)
+                    %     if norm(agents{kk}.pos - agentPos) < tc.comRange
+                    %         retry = true;
+                    %         break;
+                    %     end
+                    % end
+                    % if retry, continue; end
+
+                    % No collision with any existing agent
+                    for kk = 1:(jj - 1)
+                        if norm(agents{kk}.pos - agentPos) < agents{kk}.collisionGeometry.radius + tc.collisionRadius
+                            retry = true;
+                            break;
+                        end
+                    end
+                    if retry, continue; end
+
+                    % No collision with any obstacle
+                    for kk = 1:nObs
+                        P = min(max(agentPos, obstacles{kk}.minCorner), obstacles{kk}.maxCorner);
+                        d = agentPos - P;
+                        if dot(d, d) <= tc.collisionRadius^2
+                            retry = true;
+                            break;
+                        end
+                    end
+                end
+
+                % Initialize agent
+                collisionGeometry = collisionGeometry.initialize(agentPos, tc.collisionRadius, REGION_TYPE.COLLISION, sprintf("Agent %d Collision Region", jj));
+                agents{jj} = agents{jj}.initialize(agentPos, collisionGeometry, sensorModel, tc.comRange, tc.maxIter, tc.initialStepSize, sprintf("Agent %d", jj), tc.plotCommsGeometry);
+            end
+
+            % Randomly shuffle agents to vary index-based topology
+            agents = agents(randperm(numel(agents)));
+
+            end % reroll loop
+
+            % Inspect scenario if enabled
+            if tc.inspectScenarios
+                tc.testClass = tc.testClass.initialize(tc.testClass.domain, agents, tc.barrierGain, tc.barrierExponent, minAlt, tc.timestep, tc.maxIter, obstacles, tc.makePlots, tc.makeVideo, config.doubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
+                fprintf("Test %d (n=%d, config=%s): reinit=%d. Inspect plot.\n", testIdx, n, configKeys{configIdx}, reinitCount);
+                fprintf("To add reinits, update tc.reinit(%d) and rerun.\n", testIdx);
+                keyboard;
+                tc.testClass = tc.testClass.teardown();
+                return;
+            end
+
+            % Set up simulation
+            tc.testClass = tc.testClass.initialize(tc.testClass.domain, agents, tc.barrierGain, tc.barrierExponent, minAlt, tc.timestep, tc.maxIter, obstacles, tc.makePlots, tc.makeVideo, config.doubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
+            
+            % Save simulation parameters to output file
+            tc.testClass.writeInits();
+
+            % Run
+            tc.testClass = tc.testClass.run();
+
+            % Cleanup
+            tc.testClass = tc.testClass.teardown();
+            close all;
+        end
+        function AIIbeta_plots_3_4(tc)
+            % test-specific parameters
+            tc.makePlots = false;
+            tc.makeVideo = false;
+            maxIters = 400;
+
+            configs = results.makeConfigs();
+            c = configs.A_2_alpha;
+            c.doubleIntegrator = true; % make a2alpha into a2beta
+
+            % Set up fixed-size domain
+            minAlt = tc.domainSize(3)/10 + rand * 1/10 * tc.domainSize(3);
+            tc.testClass.domain = tc.testClass.domain.initialize([zeros(1, 3); tc.domainSize], REGION_TYPE.DOMAIN, "Domain");
+
+            % Set objective
+            objectiveMu = [tc.domainSize(1) * 2 / 3, tc.domainSize(2) * 3 / 4];
+            objectiveSigma = reshape([215, 100; 100, 175], [1, 2, 2]);
+            tc.testClass.domain.objective = tc.testClass.domain.objective.initialize(objectiveFunctionWrapper(objectiveMu, objectiveSigma), tc.testClass.domain, tc.discretizationStep, tc.protectedRange, tc.sensorPerformanceMinimum, objectiveMu, objectiveSigma);
+
+            % Set agent initial states (fully connected network of 4)
+            centerPos = [tc.domainSize(1) / 4, tc.domainSize(2) / 4];
+            d = tc.collisionRadius + (tc.comRange - tc.collisionRadius) / 4;
+            agentsPos = centerPos + [1, 1; 1, -1; -1, -1; -1, 1] / sqrt(2) * d;
+            agentAlt = minAlt * 1.5;
+            agentsPos = [agentsPos, agentAlt * ones(4, 1) + rand * 5 - 2.5];
+
+            agents = {agent, agent, agent, agent};
+            cg = spherical;
+            sensorModel = sigmoidSensor;
+            sensorModel = sensorModel.initialize(c.sensor.alphaDist, c.sensor.betaDist, c.sensor.alphaTilt, c.sensor.betaTilt);
+            agents{1} = agents{1}.initialize(agentsPos(1, :), cg.initialize(agentsPos(1, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 1 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 1", false);
+            agents{2} = agents{2}.initialize(agentsPos(2, :), cg.initialize(agentsPos(2, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 2 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 2", false);
+            agents{3} = agents{3}.initialize(agentsPos(3, :), cg.initialize(agentsPos(3, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 3 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 3", false);
+            agents{4} = agents{4}.initialize(agentsPos(4, :), cg.initialize(agentsPos(4, :), tc.collisionRadius, REGION_TYPE.COLLISION, "Agent 4 Collision Geometry"), sensorModel, tc.comRange, maxIters, tc.initialStepSize, "Agent 4", false);
+
+            obstacles = cell(1, 1);
+            obstacles{1} = rectangularPrism;
+            obstacles{1} = obstacles{1}.initialize([0, tc.domainSize(2)/2, 0; tc.domainSize(1) * 0.4, tc.domainSize(2), 40],REGION_TYPE.OBSTACLE, "Obstacle 1");
+
+            % Set up simulation
+            tc.testClass = tc.testClass.initialize(tc.testClass.domain, agents, tc.barrierGain, tc.barrierExponent, minAlt, tc.timestep, maxIters, obstacles, tc.makePlots, tc.makeVideo, c.doubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
+
+            % Save simulation parameters to output file
+            tc.testClass.writeInits();
+
+            % Run
+            tc.testClass = tc.testClass.run();
+
+            % Cleanup
+            tc.testClass = tc.testClass.teardown();
+        end
+    end
+
+    methods
+        function c = obstacleCollisionCheck(~, obstacles, obstacle)
+            % Check if the obstacle intersects with any other obstacles
+            c = false;
+            for ii = 1:size(obstacles, 1)
+                if geometryIntersects(obstacles{ii}, obstacle)
+                    c = true;
+                    return;
+                end
+            end
+        end
+
+    end
+end

test/test_miSim.m

@@ -166,8 +166,8 @@ classdef test_miSim < matlab.unittest.TestCase
                     end
 
                     % Initialize candidate agent collision geometry
-                    candidateGeometry = spherical;
+                    candidateGeometry = rectangularPrism;
-                    candidateGeometry = candidateGeometry.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
+                    candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION);
 
                     % 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));
@@ -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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [7, 6]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent};
-            geometry1 = spherical;
+            geometry1 = rectangularPrism;
-            geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
+            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);
             
             % Initialize agent sensor model with fixed parameters
             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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [3, 7]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5.2195]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             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");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
@@ -728,128 +728,6 @@ classdef test_miSim < matlab.unittest.TestCase
                   0, 0, 0, 1, 1, 1, 1;
                   0, 0, 0, 0, 0, 1, 1; ]));
         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
 
     methods

util/objectiveFunctionWrapper.m

@@ -4,16 +4,12 @@ function f = objectiveFunctionWrapper(center, sigma)
     % composite objectives in particular
     arguments (Input)
         center (:, 2) double;
-        sigma (:, 2, 2) double = reshape(eye(2), 1, 2, 2);
+        sigma (:, 2, 2) double = eye(2);
     end
     arguments (Output)
         f (1, 1) {mustBeA(f, "function_handle")};
     end
-    
-    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