results

@agent/agent.m

@@ -32,9 +32,7 @@ classdef agent
 
     properties (SetAccess = private, GetAccess = public)
         initialStepSize = NaN;
-        initialMaxAngleStepSize = NaN;
         stepDecayRate = NaN;
-        angleStepDecayRate = NaN;
     end
 
     methods (Access = public)
@@ -50,8 +48,8 @@ classdef agent
             obj.commsGeometry = spherical;
         end
         [obj] = initialize(obj, pos, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
-        [obj] = run(obj, domain, partitioning, t, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents);
+        [obj] = run(obj, domain, partitioning, t, index, agents);
-        [partitioning, agents] = partition(obj, agents, objective)
+        [partitioning] = partition(obj, agents, objective)
         [obj, f] = plot(obj, ind, f);
         updatePlots(obj);
     end

@agent/initialize.m

@@ -1,4 +1,4 @@
-function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, initialMaxAngleStepSize, label, plotCommsGeometry)
+function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, label, plotCommsGeometry)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         pos (1, 3) double;
@@ -7,7 +7,6 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
         comRange (1, 1) double;
         maxIter (1, 1) double;
         initialStepSize (1, 1) double = 0.2;
-        initialMaxAngleStepSize (1, 1) double = 5.0;
         label (1, 1) string = "";
         plotCommsGeometry (1, 1) logical = false;
     end
@@ -24,9 +23,7 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
     obj.label = label;
     obj.plotCommsGeometry = plotCommsGeometry;
     obj.initialStepSize = initialStepSize;
-    obj.initialMaxAngleStepSize = initialMaxAngleStepSize;
     obj.stepDecayRate = obj.initialStepSize / maxIter;
-    obj.angleStepDecayRate = obj.initialMaxAngleStepSize / maxIter;
 
     % Initialize performance vector
     if coder.target('MATLAB')
@@ -38,5 +35,5 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
 
     % Initialize FOV cone
     obj.fovGeometry = cone;
-    obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.halfAngle()) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label), obj.sensorModel.tilt, obj.sensorModel.azimuth);
+    obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.alphaTilt) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label));
 end

@agent/partition.m

@@ -1,4 +1,4 @@
-function [partitioning, agents] = partition(obj, agents, objective)
+function [partitioning] = partition(obj, agents, objective)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         agents (:, 1) {mustBeA(agents, "cell")};
@@ -6,7 +6,6 @@ function [partitioning, agents] = partition(obj, agents, objective)
     end
     arguments (Output)
         partitioning (:, :) double;
-        agents (:, 1) cell;
     end
 
     nAgents = size(agents, 1);
@@ -19,22 +18,8 @@ function [partitioning, agents] = partition(obj, agents, objective)
     % minimum threshold that must be exceeded for any assignment.
     agentPerf = zeros(nPoints, nAgents + 1);
     for aa = 1:nAgents
-        if isa(agents{aa}.sensorModel, "sigmoidSensor")
+        p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
-            p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
+            [objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
-                [objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
-        elseif isa(agents{aa}.sensorModel, "rfSensor")
-            otherSensorsIdx = [1:(aa - 1), (aa + 1):size(agents, 1)];
-            otherSensors = agents(otherSensorsIdx);
-            otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherSensors, "UniformOutput", false));
-            otherSensors = cellfun(@(x) x.sensorModel, otherSensors, "UniformOutput", false);
-            [p, ~, agents{aa}.sensorModel, otherSensors] = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
-                [objective.X(:), objective.Y(:), zeros(nPoints, 1)], otherSensorsPos, otherSensors);
-            for k = 1:numel(otherSensorsIdx)
-                agents{otherSensorsIdx(k)}.sensorModel = otherSensors{k};
-            end
-        else
-            error("?");
-        end
         agentPerf(:, aa) = p(:);
     end
     agentPerf(:, nAgents + 1) = objective.sensorPerformanceMinimum;

@agent/run.m

@@ -1,15 +1,14 @@
-function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents)
+function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useDoubleIntegrator, dampingCoeff, dt)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         domain (1, 1) {mustBeGeometry};
         partitioning (:, :) double;
         timestepIndex (1, 1) double;
         index (1, 1) double;
+        agents (:, 1) {mustBeA(agents, "cell")};
         useDoubleIntegrator (1, 1) logical = false;
         dampingCoeff (1, 1) double = 2.0;
         dt (1, 1) double = 1.0;
-        optimizeSensorPointing (1, 1) logical = false;
-        otherAgents (:, 1) cell = cell();
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "agent")};
@@ -34,62 +33,33 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
     maskedX = domain.objective.X(partitionMask);
     maskedY = domain.objective.Y(partitionMask);
 
-    if isa(obj.sensorModel, "rfSensor")
+    % Compute agent performance at the current position and each delta position +/- X, Y, Z
-        % Extract other agents' sensor models and positions once, outside the delta loop.
+    delta = domain.objective.discretizationStep; % smallest possible step size that gets different results
-        % Mask the full-grid RSS caches (filled by partition()) down to this agent's
+    deltaApplicator = [0, 0, 0; 1, 0, 0; -1, 0, 0; 0, 1, 0; 0, -1, 0; 0, 0, 1; 0, 0, -1]; % none, +X, -X, +Y, -Y, +Z, -Z
-        % partition subset so sensorPerformance can reuse them for all perturbations.
+    C_delta = NaN(7, 1); % agent performance at delta steps in each direction
-        otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherAgents, "UniformOutput", false));
+    for ii = 1:7
-        otherSensors    = cellfun(@(x) x.sensorModel, otherAgents, "UniformOutput", false);
-        partitionIndices = find(partitionMask);
-        for kk = 1:numel(otherSensors)
-            if ~isempty(otherSensors{kk}.rssCache)
-                otherSensors{kk}.rssCache = otherSensors{kk}.rssCache(partitionIndices);
-            end
-        end
-        % Pre-mask this agent's own full-grid cache to the partition subset.
-        % Used for ii==1 (current position, no perturbation) to avoid recomputing.
-        baseSensorModel = obj.sensorModel;
-        if ~isempty(obj.sensorModel.rssCache)
-            baseSensorModel.rssCache = obj.sensorModel.rssCache(partitionIndices);
-        end
-    end
-
-    if optimizeSensorPointing
-        % Stash actual current sensor model tilt/azimuth before messing with it
-        % in these following hypotheticals
-        tilt = obj.sensorModel.tilt;
-        azimuth = obj.sensorModel.azimuth;
-    end
-
-    % Compute agent performance at the current position and each delta position +/- X, Y, Z, tilt, azimuth
-    deltaPos = domain.objective.discretizationStep; % smallest possible step size that gets different results
-    if optimizeSensorPointing
-        deltaAngle = atan2d(domain.objective.discretizationStep, obj.pos(3)); % smallest possible angle derived from smallest possible step size and current height
-    end
-    deltaApplicator = [0, 0, 0, 0, 0; 1, 0, 0, 0, 0; -1, 0, 0, 0, 0; 0, 1, 0, 0, 0; 0, -1, 0, 0, 0; 0, 0, 1, 0, 0; 0, 0, -1, 0, 0; 0, 0, 0, 1, 0; 0, 0, 0, -1, 0; 0, 0, 0, 0, 1; 0, 0, 0, 0, -1;]; % none, +X, -X, +Y, -Y, +Z, -Z, +tilt, -tilt, +azimuth, -azimuth
-    C_delta = NaN(size(deltaApplicator, 1), 1); % agent performance at delta steps in each direction
-    for ii = 1:size(deltaApplicator, 1)
-        if ~optimizeSensorPointing && ii > 7; break; end
         % Apply delta to position
-        pos = obj.pos + deltaPos * deltaApplicator(ii, 1:3);
+        pos = obj.pos + delta * deltaApplicator(ii, 1:3);
-        if optimizeSensorPointing
-            % Apply delta to tilt and azimuth
-            obj.sensorModel.tilt = tilt + deltaAngle * deltaApplicator(ii, 4);
-            obj.sensorModel.azimuth = azimuth + deltaAngle * deltaApplicator(ii, 5);
-        end
         
         % Compute performance values on partition
-        if isa(obj.sensorModel, "sigmoidSensor")
+        if ii < 6
+            % Compute sensing performance
             sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
-        elseif isa(obj.sensorModel, "rfSensor")
+            % Objective performance does not change for 0, +/- X, +/- Y steps.
-            if ii == 1
+            % Those values are computed once before the loop and are only
-                sensorModelForDelta = baseSensorModel; % reuse partition-step cache; no recompute needed
+            % recomputed when +/- Z steps are applied
-            else
-                sensorModelForDelta = obj.sensorModel.clearRssCache;
-            end
-            [sensorValues, ~, ~, ~] = sensorModelForDelta.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))], otherSensorsPos, otherSensors);
         else
-            error("?");
+            % Redo partitioning for Z stepping only
+            partitioning = obj.partition(agents, domain.objective);
+
+            % Recompute partiton-derived performance values for objective
+            partitionMask = partitioning == index;
+            objectiveValues = domain.objective.values(partitionMask); % f(omega) on W_n
+
+            % Recompute partiton-derived performance values for sensing
+            maskedX = domain.objective.X(partitionMask);
+            maskedY = domain.objective.Y(partitionMask);
+            sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
         end
 
         % Rearrange data into image arrays
@@ -103,54 +73,37 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
         C_delta(ii) = sum(C(~isnan(C)));
     end
 
-    if optimizeSensorPointing
-        % Reset sensor model to actual tilt and azimuth angles
-        obj.sensorModel.tilt = tilt;
-        obj.sensorModel.azimuth = azimuth;
-    end
-
     % Store agent performance at current time and place
     if coder.target('MATLAB')
         obj.performance(timestepIndex + 1) = C_delta(1);
     end
 
     % Compute gradient by finite central differences
-    gradC = [(C_delta(2)-C_delta(3))/(2*deltaPos), (C_delta(4)-C_delta(5))/(2*deltaPos), (C_delta(6)-C_delta(7))/(2*deltaPos)];
+    gradC = [(C_delta(2)-C_delta(3))/(2*delta), (C_delta(4)-C_delta(5))/(2*delta), (C_delta(6)-C_delta(7))/(2*delta)];
-    if optimizeSensorPointing
-        gradC(4) = (C_delta(8) -C_delta(9)) /(2*deltaAngle);
-        gradC(5) = (C_delta(10)-C_delta(11))/(2*deltaAngle);
-    end
 
     % Compute scaling factor
-    targetPosRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
+    targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
-    gradPosNorm = norm(gradC(1:3));
+    gradNorm = norm(gradC);
 
     % Compute unconstrained next state
     if useDoubleIntegrator
         % Double-integrator: gradient produces desired acceleration with damping
-        if gradPosNorm < 1e-100
+        if gradNorm < 1e-100
-            a_gradient = zeros(1, 5);
+            a_gradient = zeros(1, 3);
         else
             % Scale so steady-state step ≈ targetRate (matching SI behavior)
-            a_gradient = (targetPosRate * dampingCoeff / (gradPosNorm * dt)) * gradC;
+            a_gradient = (targetRate * dampingCoeff / (gradNorm * dt)) * gradC;
         end
         % Semi-implicit Euler: unconditionally stable for any dampingCoeff and dt
-        obj.vel = (obj.vel + a_gradient(1:3) * dt) / (1 + dampingCoeff * dt);
+        obj.vel = (obj.vel + a_gradient * dt) / (1 + dampingCoeff * dt);
         obj.pos = obj.lastPos + obj.vel * dt;
     else
         % Single-integrator: gradient directly sets position step
-        if gradPosNorm >= 1e-100
+        if gradNorm >= 1e-100
-            obj.pos = obj.pos + (targetPosRate / gradPosNorm) * gradC(1:3);
+            obj.pos = obj.pos + (targetRate / gradNorm) * gradC;
         end
     end
 
-    % Update tilt and azimuth, saturating at the decaying maximum allowed step size
-    if optimizeSensorPointing
-        maxAngleStep = obj.initialMaxAngleStepSize - obj.angleStepDecayRate * timestepIndex;
-        obj.sensorModel.tilt    = obj.sensorModel.tilt    + sign(gradC(4)) * min(abs(gradC(4)), maxAngleStep);
-        obj.sensorModel.azimuth = obj.sensorModel.azimuth + sign(gradC(5)) * min(abs(gradC(5)), maxAngleStep);
-    end
-
     % Reinitialize collision geometry in the new position
     d = obj.pos - obj.collisionGeometry.center;
     if isa(obj.collisionGeometry, "rectangularPrism")

@agent/updatePlots.m

@@ -7,68 +7,45 @@ function updatePlots(obj)
 
     % Find change in agent position since last timestep
     deltaPos = obj.pos - obj.lastPos;
-    posChanged    = ~(all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3)));
+    if all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3))
-    orientChanged = obj.sensorModel.tilt    ~= obj.fovGeometry.tilt || ...
+        % Agent did not move, so nothing has to move on the plots
-                    obj.sensorModel.azimuth ~= obj.fovGeometry.azimuth;
-
-    if ~posChanged && ~orientChanged
         return;
     end
 
-    if posChanged
+    % Scatterplot point positions
-        % Scatterplot point positions
+    for ii = 1:size(obj.scatterPoints, 1)
-        for ii = 1:size(obj.scatterPoints, 1)
+        obj.scatterPoints(ii).XData = obj.pos(1);
-            obj.scatterPoints(ii).XData = obj.pos(1);
+        obj.scatterPoints(ii).YData = obj.pos(2);
-            obj.scatterPoints(ii).YData = obj.pos(2);
+        obj.scatterPoints(ii).ZData = obj.pos(3);
-            obj.scatterPoints(ii).ZData = obj.pos(3);
+    end
-        end
 
-        % Collision geometry edges
+    % Collision geometry edges
-        for jj = 1:size(obj.collisionGeometry.lines, 2)
+    for jj = 1:size(obj.collisionGeometry.lines, 2)
+        % Update plotting
+        for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
+            obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
+            obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
+            obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
+        end
+    end
+
+    % Communications geometry edges
+    if obj.plotCommsGeometry
+        for jj = 1:size(obj.commsGeometry.lines, 2)
             for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
                 obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
                 obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
                 obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
             end
         end
-
-        % Communications geometry edges
-        if obj.plotCommsGeometry
-            for jj = 1:size(obj.commsGeometry.lines, 2)
-                for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
-                    obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
-                    obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
-                    obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
-                end
-            end
-        end
     end
 
-    % FOV cone: recompute full mesh whenever position or orientation changes
+    % Update FOV geometry surfaces
-    if ~isempty(obj.fovGeometry.surface)
+    for jj = 1:size(obj.fovGeometry.surface, 2)
-        % Sync fovGeometry state to current agent position and sensor orientation
+        % Update each plot
-        obj.fovGeometry = obj.fovGeometry.initialize( ...
+        % obj.fovGeometry = obj.fovGeometry.plot(obj.spatialPlotIndices)
-            obj.pos, obj.fovGeometry.radius, obj.fovGeometry.height, ...
+        obj.fovGeometry.surface(jj).XData = obj.fovGeometry.surface(jj).XData + deltaPos(1);
-            obj.fovGeometry.tag, obj.fovGeometry.label, ...
+        obj.fovGeometry.surface(jj).YData = obj.fovGeometry.surface(jj).YData + deltaPos(2);
-            obj.sensorModel.tilt, obj.sensorModel.azimuth);
+        obj.fovGeometry.surface(jj).ZData = obj.fovGeometry.surface(jj).ZData + deltaPos(3);
-
-        % Recompute cone mesh (mirrors cone.plot logic)
-        maxAlt = obj.fovGeometry.surface(1).Parent.ZLim(2);
-        scalingFactor = maxAlt / obj.fovGeometry.height;
-        [X, Y, Z] = cylinder([scalingFactor * obj.fovGeometry.radius, 0], obj.fovGeometry.n);
-        Z = Z * maxAlt;
-        Ry = [cosd(obj.fovGeometry.tilt), 0, -sind(obj.fovGeometry.tilt); 0, 1, 0; sind(obj.fovGeometry.tilt), 0, cosd(obj.fovGeometry.tilt)];
-        Rz = [sind(obj.fovGeometry.azimuth), -cosd(obj.fovGeometry.azimuth), 0; cosd(obj.fovGeometry.azimuth), sind(obj.fovGeometry.azimuth), 0; 0, 0, 1];
-        R  = Rz * Ry;
-        pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
-        X = reshape(pts(1, :), size(X)) + obj.pos(1);
-        Y = reshape(pts(2, :), size(Y)) + obj.pos(2);
-        Z = reshape(pts(3, :) + maxAlt, size(Z)) + obj.pos(3) - maxAlt;
-
-        for jj = 1:size(obj.fovGeometry.surface, 2)
-            obj.fovGeometry.surface(jj).XData = X;
-            obj.fovGeometry.surface(jj).YData = Y;
-            obj.fovGeometry.surface(jj).ZData = Z;
-        end
     end
 end

@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));
-	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);
-	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)
@@ -132,10 +128,13 @@ 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];
-	    obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
+        idx = idx + 6;
-        end
+    end
-	idx = idx + 6;
+
+    if coder.target('MATLAB')
+        % Save off h function values (logging only — not needed in compiled mode)
+        obj.h(:, obj.timestepIndex) = [h(triu(true(nAgents), 1)); reshape(hObs, [], 1); h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax;];
     end
 
     % Add communication network constraints
@@ -165,10 +164,7 @@ function [obj] = constrainMotion(obj)
             end
         end
     end
-    
+    obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
-    if coder.target('MATLAB')
-	obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
-    end
 
     % Double-integrator: transform QP from velocity to acceleration space.
     % Single-integrator constraint: A * v <= b

@miSim/initialize.m

@@ -1,4 +1,4 @@
-function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology, optimizeSensorPointing)
+function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "miSim")};
         domain (1, 1) {mustBeGeometry};
@@ -14,7 +14,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
         useDoubleIntegrator (1, 1) logical = false;
         dampingCoeff (1, 1) double = 2.0;
         useFixedTopology (1, 1) logical = false;
-        optimizeSensorPointing (1, 1) logical = false;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "miSim")};
@@ -94,7 +93,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
     obj.useDoubleIntegrator = useDoubleIntegrator;
     obj.dampingCoeff = dampingCoeff;
     obj.useFixedTopology = useFixedTopology;
-    obj.optimizeSensorPointing = optimizeSensorPointing;
 
     % Compute adjacency matrix and network topology
     obj = obj.updateAdjacency();
@@ -111,6 +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
@@ -138,12 +138,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
         % Initialize variable that will store barrier function values per timestep for analysis purposes
         obj.barriers = NaN(obj.numBarriers, size(obj.times, 1));
 
-        % Initialize constraint adjacency history (nAgents x nAgents x nTimesteps)
-        nAgents = size(obj.agents, 1);
-        obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
-        obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
-
-
         % Set up plots showing initialized state
         obj = obj.plot();
 

@miSim/initializeFromCsv.m

@@ -52,19 +52,8 @@ BETA_TILT_VEC        = scenario.betaTilt;           % 1×N
 
 DOMAIN_MIN                 = scenario.domainMin;                % 1×3
 DOMAIN_MAX                 = scenario.domainMax;                % 1×3
-
+OBJECTIVE_GROUND_POS       = scenario.objectivePos;             % 1×2
-% objectivePos: 2 values per Gaussian component (1 or 2 components supported)
+OBJECTIVE_VAR              = reshape(scenario.objectiveVar, 2, 2); % 2×2 covariance matrix
-nObjComponents = numel(scenario.objectivePos) / 2;
-assert(mod(numel(scenario.objectivePos), 2) == 0, ...
-    'objectivePos must have an even number of values (2 per Gaussian component)');
-assert(nObjComponents >= 1 && nObjComponents <= 2, ...
-    'At most 2 objective Gaussian components supported; got %d', nObjComponents);
-assert(numel(scenario.objectiveVar) == nObjComponents * 4, ...
-    'objectiveVar must have %d values for %d component(s); got %d', ...
-    nObjComponents * 4, nObjComponents, numel(scenario.objectiveVar));
-OBJECTIVE_GROUND_POS = reshape(scenario.objectivePos, 2, nObjComponents)';           % nObj×2
-OBJECTIVE_VAR        = permute(reshape(scenario.objectiveVar, 2, 2, nObjComponents), [3, 1, 2]); % nObj×2×2
-
 SENSOR_PERFORMANCE_MINIMUM = scenario.sensorPerformanceMinimum; % scalar
 
 % Initial UAV positions: flat vector reshaped to N×3

@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

@@ -20,7 +20,6 @@ classdef miSim
         useDoubleIntegrator = false; % false = single-integrator, true = double-integrator dynamics
         dampingCoeff = 2.0; % velocity-proportional damping for double-integrator mode
         useFixedTopology = false; % false = lesser neighbor (dynamic), true = fixed initial topology
-        optimizeSensorPointing = false; % false = fixed sensor tilt/azimuth, true = optimize tilt/azimuth via gradient ascent
         artifactName = "";
         f; % main plotting tiled layout figure
         fPerf; % performance plot figure
@@ -28,7 +27,6 @@ classdef miSim
         spatialPlotIndices = [6, 4, 3, 2];
         numBarriers = 0; % Number of barrier functions needed
         barriers = []; % log barrier function values at each timestep for analysis
-        constraintAdjacencyHist = []; % log constraint adjacency matrix at each timestep
     end
 
     properties (Access = private)
@@ -55,6 +53,7 @@ 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
@@ -70,10 +69,8 @@ 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

@@ -10,13 +10,7 @@ function [obj] = run(obj)
         % Start video writer
         if obj.makeVideo
             v = obj.setupVideoWriter();
-            drawnow;
             v.open();
-            % Capture reference frame size; used to resize frames that deviate
-            % due to figure reflow during plot updates (e.g. in headless mode).
-            I_ref = getframe(obj.f);
-            v.writeVideo(I_ref);
-            videoFrameSize = [size(I_ref.cdata, 2), size(I_ref.cdata, 1)];
         end
     end
 
@@ -31,31 +25,19 @@ function [obj] = run(obj)
             obj.validate();
         end
 
-        % Clear RF sensor caches
-        if isa(obj.agents{1}.sensorModel, "rfSensor")
-            for ss = 1:size(obj.agents, 1)
-                obj.agents{ss}.sensorModel = obj.agents{ss}.sensorModel.clearRssCache;
-            end
-        end
-
         % Update partitioning before moving (this one is strictly for
         % plotting purposes, the real partitioning is done by the agents)
-        [obj.partitioning, obj.agents] = obj.agents{1}.partition(obj.agents, obj.domain.objective);
+        obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
 
         % Determine desired communications links
         if ~obj.useFixedTopology
             obj = obj.lesserNeighbor();
         end
 
-        % Log constraint adjacency for this timestep
-        if coder.target('MATLAB')
-            obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
-        end
-
         % Moving
         % Iterate over agents to simulate their unconstrained motion
         for jj = 1:size(obj.agents, 1)
-            obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep, obj.optimizeSensorPointing, obj.agents([1:(jj - 1), (jj + 1):size(obj.agents, 1)]));
+            obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep);
         end
 
         % Adjust motion determined by unconstrained gradient ascent using
@@ -79,9 +61,6 @@ function [obj] = run(obj)
             % Write frame in to video
             if obj.makeVideo
                 I = getframe(obj.f);
-                if size(I.cdata, 2) ~= videoFrameSize(1) || size(I.cdata, 1) ~= videoFrameSize(2)
-                    I.cdata = imresize(I.cdata, [videoFrameSize(2), videoFrameSize(1)]);
-                end
                 v.writeVideo(I);
             end
         end

@miSim/teardown.m

@@ -20,7 +20,6 @@ function obj = teardown(obj)
     out.dampingCoeff = obj.dampingCoeff;
     out.useDoubleIntegrator = obj.useDoubleIntegrator;
     out.useFixedTopology = obj.useFixedTopology;
-    out.constraintAdjacency = obj.constraintAdjacencyHist(:, :, 1:(end - 1));
     for ii = 1:size(obj.agents, 1)
         out.agent(ii).pos = squeeze(obj.posHist(ii, 1:(end - 1), 1:3));
         out.agent(ii).vel = squeeze(obj.velHist(ii, 1:(end - 1), 1:3));
@@ -44,7 +43,6 @@ function obj = teardown(obj)
     obj.agents = cell(0, 1);
     obj.adjacency = NaN;
     obj.constraintAdjacencyMatrix = NaN;
-    obj.constraintAdjacencyHist = [];
     obj.partitioning = NaN;
     obj.performance = 0;
     obj.barrierGain = NaN;

@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

@@ -5,66 +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);
-    if isprop(obj.agents{1}.sensorModel, "alphaDist")
+    alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
-        % sigmoidSensor parameters
+    betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
-        alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
+    alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
-        betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
+    betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
-        alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
-        betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
-
-        % others to zero
-        lossExponent = zeros(size(obj.agents));
-        P_TX = zeros(size(obj.agents));
-        BW = zeros(size(obj.agents));
-        f_c = zeros(size(obj.agents));
-        G_RX_dBi = zeros(size(obj.agents));
-        beamwidthExponent = zeros(size(obj.agents));
-        
-    elseif isprop(obj.agents{1}.sensorModel, "P_TX")
-        % rfSensor parameters
-        lossExponent = cellfun(@(x) x.sensorModel.lossExponent, obj.agents);
-        P_TX = cellfun(@(x) x.sensorModel.P_TX, obj.agents);
-        BW = cellfun(@(x) x.sensorModel.BW, obj.agents);
-        f_c = cellfun(@(x) x.sensorModel.f_c, obj.agents);
-        G_RX_dBi = cellfun(@(x) x.sensorModel.G_RX_dBi, obj.agents);
-        beamwidthExponent = cellfun(@(x) x.sensorModel.beamwidthExponent, obj.agents);
-
-        % others to zero
-        alphaDist = zeros(size(obj.agents));
-        betaDist = zeros(size(obj.agents));
-        alphaTilt = zeros(size(obj.agents));
-        betaTilt = zeros(size(obj.agents));
-    end
-    % joint parameters
-    tilt = cellfun(@(x) x.sensorModel.tilt, obj.agents);
-    azimuth = cellfun(@(x) x.sensorModel.azimuth, obj.agents);
     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, ...
-                    "tilt", tilt, "azimuth", azimuth, ... % joint sensor parameters
+                    "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
-                    "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ... % sigmoid sensor parameters
-                    "lossExponent", lossExponent, "P_TX", P_TX, "BW", BW, "f_c", f_c, "G_RX_dBi", G_RX_dBi, "beamwidthExponent", beamwidthExponent, ... % RF sensor parameters
                     ... % ^^^ 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(:)));
 

@rfSensor/RSS.m

@@ -1,24 +0,0 @@
-function value = RSS(obj, d, dx, dy, dz)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        d  (:, 1) double;
-        dx (:, 1) double;
-        dy (:, 1) double;
-        dz (:, 1) double;
-    end
-    arguments (Output)
-        value (:, 1) double
-    end
-    % Boresight unit vector: [st*sa, st*ca, -ct]
-    % Target direction unit vector: [dx, dy, dz] / d
-    % cos_theta = dot product of the two, computed without per-point trig.
-    st = sind(obj.tilt);
-    ct = cosd(obj.tilt);
-    sa = sind(obj.azimuth);
-    ca = cosd(obj.azimuth);
-    cos_theta = (st .* (dx .* sa + dy .* ca) - ct .* dz) ./ max(d, eps);
-    cos_theta = max(-1, min(1, cos_theta));
-    theta = acosd(cos_theta);
-    gain  = 10 .* obj.beamwidthExponent .* log10((1 + cosd(theta)) ./ 2);
-    value = obj.P_TX_dBm + gain + obj.G_RX_dBi - obj.pathLoss(d);
-end

@rfSensor/clearRssCache.m

@@ -1,11 +0,0 @@
-function obj = clearRssCache(obj)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-    end
-    arguments (Output)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-    end
-
-    obj.rssCache = double.empty(0, 1);
-
-end

@rfSensor/computePointToPoints.m

@@ -1,6 +0,0 @@
-function [d, dx, dy, dz] = computePointToPoints(~, agentPos, targetPos)
-    dx = targetPos(:,1) - agentPos(1);
-    dy = targetPos(:,2) - agentPos(2);
-    dz = targetPos(:,3) - agentPos(3);
-    d  = sqrt(dx.^2 + dy.^2 + dz.^2);
-end

@rfSensor/halfAngle.m

@@ -1,23 +0,0 @@
-function value = halfAngle(obj)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-    end
-    arguments (Output)
-        value (1, 1) double;
-    end
-    % Sweep angular offset from boresight by evaluating transmitterGain at
-    % (obj.tilt + dtheta, obj.azimuth). The cosine difference identity guarantees
-    % the resulting angular offset from boresight equals dtheta exactly,
-    % independent of the actual pointing direction.
-    dtheta = (0:0.1:179.9)';
-    gain = obj.transmitterGain(obj.tilt + dtheta, obj.azimuth * ones(size(dtheta)));
-    target = gain(1) - 3;
-    idx = find(gain <= target, 1);
-    if isempty(idx) || idx == 1
-        value = dtheta(end);
-        return;
-    end
-    % Linear interpolation between bracketing samples
-    value = dtheta(idx-1) + (target - gain(idx-1)) * ...
-            (dtheta(idx) - dtheta(idx-1)) / (gain(idx) - gain(idx-1));
-end

@rfSensor/initialize.m

@@ -1,32 +0,0 @@
-function obj = initialize(obj, txPower, bandwidth, centerFreq, rxGain_dBi, beamwidthExponent, tilt, azimuth, lossExponent)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")}
-        txPower (1, 1) double;
-        bandwidth (1, 1) double;
-        centerFreq (1, 1) double;
-        rxGain_dBi (1, 1) double;
-        beamwidthExponent (1, 1) double;
-        tilt (1, 1) double = 0;
-        azimuth (1, 1) double = 0;
-        lossExponent (1, 1) double = NaN;
-    end
-    arguments (Output)
-        obj (1, 1) {mustBeA(obj, "rfSensor")}
-    end
-
-    %% Provided values
-    obj.P_TX = txPower; % Transmit power (W)
-    obj.BW = bandwidth; % Bandwidth (Hz)
-    obj.f_c = centerFreq; % Center frequency (Hz)
-    obj.G_RX_dBi = rxGain_dBi; % Receiving Antenna Gain (dBi)
-    obj.beamwidthExponent = beamwidthExponent; % Defines how focused the antenna beam is
-    obj.lossExponent = lossExponent;
-
-    % Define initial antenna pointing
-    obj.tilt = tilt;
-    obj.azimuth = azimuth;
-
-    %% Computed values
-    obj.P_TX_dBm = 10*log10(obj.P_TX/1e-3); % Transmit power in dBm
-    obj.N = obj.k_B * obj.T_0 * obj.BW; % Thermal noise
-end

@rfSensor/pathLoss.m

@@ -1,13 +0,0 @@
-function L_FSPL_dB = pathLoss(obj, d)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        d (:, 1) double; % distance from TX to RX
-    end
-    arguments (Output)
-        L_FSPL_dB (:, 1) double
-    end
-
-    % Free Space Path Loss (dB); d clamped away from zero (log undefined at d=0)
-    L_FSPL_dB = obj.lossExponent * 10 * log10(max(d, eps)) + 20 * log10(obj.f_c) + 20 * log10((4*pi)/obj.c);
-
-end

@rfSensor/plot.m

@@ -1,125 +0,0 @@
-function f = plot(obj, altitude, otherSensorsPos, otherSensors)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        altitude (1, 1) double;
-        otherSensorsPos (:, 3) double = NaN(0, 3);
-        otherSensors (:, 1) cell = cell(0, 1);
-    end
-    arguments (Output)
-        f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
-    end
-
-    % Clear local caches so this visualization always uses its own grid
-    obj.rssCache = [];
-    for ii = 1:numel(otherSensors)
-        otherSensors{ii}.rssCache = [];
-    end
-
-    % bias other sensors altitudes appropriately
-    otherSensorsPos = otherSensorsPos + [0, 0, altitude];
-
-    % Create grid on which to evalute SINR, SNR
-    agentPos = [0, 0, altitude];
-    d = 10;
-    if ~isempty(otherSensorsPos)
-        d = max(otherSensorsPos(:, 3) * 0.55);
-        d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
-    end
-    c = 0.1;
-    d = ceil(d / c) * c;
-    distances = -d:c:d;
-    [targetPosX, targetPosY] = meshgrid(distances, distances);
-
-    % Compute SINR, SNR
-    [SINR, ~] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
-    SINR = reshape(SINR, size(targetPosX));
-
-    % normalize in linear scale
-    % SINR = 10.^(SINR/10); SINR = SINR ./ max(SINR(:)); SINR = 10 * log10(SINR);
-
-    % Collect sensor positions and boresight parameters for overlay
-    sensorTilts   = [obj.tilt;    cellfun(@(s) s.tilt,    otherSensors)];
-    sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
-    tailScale = 0.5 * d;
-
-    f = figure;
-    surf(targetPosX, targetPosY, zeros(size(targetPosX)), SINR, "EdgeColor", "none");
-    axis(f.Children(1), "image");
-    colormap(f.Children(1), "hot");
-    title("Ground User SINR and -3 dB antenna gain regions");
-    subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
-    c = colorbar;
-    ylabel(c, "SINR (dB)");
-    xlabel("X (m)");
-    ylabel("Y (m)");
-    hold(f.Children(2), "on");
-    scatter3(0, 0, altitude, 100, 'ko', "LineWidth", 2);
-    scatter3(otherSensorsPos(:, 1), otherSensorsPos(:, 2), otherSensorsPos(:, 3), 100, "bx", "LineWidth", 2);
-    qSelf = quiver3(0, 0, altitude, ...
-        tailScale * sind(obj.tilt) * sind(obj.azimuth), ...
-        tailScale * sind(obj.tilt) * cosd(obj.azimuth), ...
-        -tailScale * cosd(obj.tilt), ...
-        0, 'k', 'LineWidth', 1.5);
-    qSelf.MaxHeadSize = 0.75;
-    if ~isempty(otherSensors)
-        qOthers = quiver3(otherSensorsPos(:,1), otherSensorsPos(:,2), otherSensorsPos(:,3), ...
-            tailScale .* sind(sensorTilts(2:end)) .* sind(sensorAzimuths(2:end)), ...
-            tailScale .* sind(sensorTilts(2:end)) .* cosd(sensorAzimuths(2:end)), ...
-            -tailScale .* cosd(sensorTilts(2:end)), ...
-            0, 'b', 'LineWidth', 1.5);
-        qOthers.MaxHeadSize = 0.75;
-    end
-    % Draw half-angle cones co-boresighted with each quiver arrow
-    N = 48;
-    phi = linspace(0, 2*pi, N);
-    [PHI, S] = meshgrid(phi, [0; 1]);   % row 1 = apex (s=0), row 2 = base (s=1)
-    allSensors = [{obj}; otherSensors];
-    allPos     = [[0, 0, altitude]; otherSensorsPos];
-    for ii = 1:numel(allSensors)
-        ha  = allSensors{ii}.halfAngle();
-        tlt = sensorTilts(ii);
-        az  = sensorAzimuths(ii);
-        pos = allPos(ii, :);
-        % Cone length: enough that the axis tip is guaranteed below z=0
-        coneLength = 1.1 * pos(3) / max(cosd(tlt), 0.1);
-        % Nadir cone mesh: apex at origin, base at z = -coneLength
-        cX = S .* coneLength .* tand(ha) .* cos(PHI);
-        cY = S .* coneLength .* tand(ha) .* sin(PHI);
-        cZ = -S .* coneLength;
-        % Rotate nadir → boresight (same convention as quiver arrows)
-        Ry = [cosd(tlt), 0, -sind(tlt); 0, 1, 0; sind(tlt), 0, cosd(tlt)];
-        Rz = [sind(az), -cosd(az), 0; cosd(az), sind(az), 0; 0, 0, 1];
-        R  = Rz * Ry;
-        pts = R * [cX(:)'; cY(:)'; cZ(:)'];
-        cX  = reshape(pts(1,:), size(cX)) + pos(1);
-        cY  = reshape(pts(2,:), size(cY)) + pos(2);
-        cZ  = reshape(pts(3,:), size(cZ)) + pos(3);
-        if ii == 1
-            fc = [0, 0, 0];
-        else
-            fc = [0, 0, 1];
-        end
-        surf(cX, cY, cZ, "FaceColor", fc, "FaceAlpha", 0.15, "EdgeColor", "none");
-
-        % Conic section: intersect each cone generator with z=0
-        b_vec = R * [0; 0; -1];
-        u_vec = R * [1; 0; 0];
-        v_vec = R * [0; 1; 0];
-        phi_sec = linspace(0, 2*pi, 720)';
-        dirs = cosd(ha) .* b_vec' + sind(ha) .* (cos(phi_sec) .* u_vec' + sin(phi_sec) .* v_vec');
-        t_sec = -pos(3) ./ dirs(:, 3);
-        t_sec(t_sec <= 0) = NaN;
-        sx = pos(1) + t_sec .* dirs(:, 1);
-        sy = pos(2) + t_sec .* dirs(:, 2);
-        plot3(sx, sy, zeros(size(sx)), "Color", fc, "LineWidth", 2);
-    end
-    clim(f.Children(2), [min(SINR(:)), max(SINR(:))]);
-    xlim(f.Children(2), [-d, d]);
-    ylim(f.Children(2), [-d, d]);
-    hold(f.Children(2), "off");
-    zlim([0, Inf]);
-    
-
-
-
-end

@rfSensor/plotParameters.m

@@ -1,52 +0,0 @@
-function f = plotParameters(obj)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-    end
-    arguments (Output)
-        f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
-    end
-
-    % Agent altitude layers and angle sample points
-    alt_values = 10.^[1, 2, 3, 4];
-    t_values = 0:2.5:87.5;   % 0=nadir (center), <90=near horizon (edge)
-    a_values = 0:2.5:360;
-
-    [T, A] = meshgrid(t_values, a_values);   % Naz x Nel
-    Ar = deg2rad(A);
-
-    f = figure;
-    hold("on");
-
-    for ii = 1:numel(alt_values)
-        alt = alt_values(ii);
-
-        % For agent at altitude alt, ground target at tilt T has slant distance:
-        D = alt ./ cosd(T);
-
-        % Compute RSS for each (d, t, a) triple
-        rss = obj.RSS(D(:), T(:), A(:));
-        Fslice = reshape(rss, size(D));
-
-        % Disc geometry: t=0 (nadir) -> center, t~90 (horizon) -> edge
-        r = log10(alt) .* T ./ 90;
-        X = r .* cos(Ar);
-        Y = r .* sin(Ar);
-        Z = log10(alt) * ones(size(X));
-
-        hs = surf(X, Y, Z, Fslice);
-        hs.EdgeColor = 'none';
-        hs.FaceColor = 'interp';
-        hs.FaceAlpha = 0.25;
-    end
-
-    colormap(turbo);
-    c = colorbar; c.Label.String = "Received Signal Strength (dB)";
-    daspect([1 1 0.2]);
-    xlabel('X (log_{10} units)'); ylabel('Y (log_{10} units)'); zlabel('log_{10} Altitude (m)');
-    set(gca, 'ZDir', 'reverse');
-    view(3);
-    axis("vis3d");
-    grid("on");
-    scatter3(0, 0, 0, 'rx');
-    hold("off");
-end

@rfSensor/plotPerformance.m

@@ -1,91 +0,0 @@
-function f = plotPerformance(obj, altitude, otherSensorsPos, otherSensors)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        altitude (1, 1) double;
-        otherSensorsPos (:, 3) double = NaN(0, 3);
-        otherSensors (:, 1) cell = cell(0, 1);
-    end
-    arguments (Output)
-        f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
-    end
-
-    % Clear local caches so this visualization always uses its own grid
-    obj.rssCache = [];
-    for ii = 1:numel(otherSensors)
-        otherSensors{ii}.rssCache = [];
-    end
-
-    % bias other sensors altitudes appropriately
-    otherSensorsPos = otherSensorsPos + [0, 0, altitude];
-
-    % Create grid on which to evalute SINR, SNR
-    agentPos = [0, 0, altitude];
-    d = 10;
-    if ~isempty(otherSensorsPos)
-        d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
-    end
-    c = 0.1;
-    d = ceil(d / c) * c;
-    distances = -d:c:d;
-    [targetPosX, targetPosY] = meshgrid(distances, distances);
-
-    % Compute SINR, SNR
-    [SINR, SNR] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
-    SINR = reshape(SINR, size(targetPosX));
-    SNR = reshape(SNR, size(targetPosX));
-
-    % normalize in linear scale
-    SINR = 10.^(SINR/10); SINR = SINR ./ max(SINR(:)); SINR = 10 * log10(SINR);
-    SNR  = 10.^(SNR/10);  SNR  = SNR  ./ max(SNR(:));  SNR  = 10 * log10(SNR);
-
-    % Collect sensor positions and boresight parameters for overlay
-    sensorXY      = [0, 0; otherSensorsPos(:, 1:2)];
-    sensorTilts   = [obj.tilt;    cellfun(@(s) s.tilt,    otherSensors)];
-    sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
-    tailScale = 0.5 * d;
-
-    f = figure;
-    tiledlayout(1, 2, TileSpacing="compact", Padding="compact");
-
-    nexttile;
-    imagesc(distances, distances, SNR);
-    axis("image"); set(gca, 'YDir', 'normal');
-    colorbar; xlabel("X (m)"); ylabel("Y (m)");
-    title("Linearly Normalized SNR (dB)");
-    subtitle("No interfering sources");
-    addSensorOverlay(gca, sensorXY(1, 1:2), sensorTilts(1, 1), sensorAzimuths(1, 1), tailScale);
-
-    nexttile;
-    imagesc(distances, distances, SINR);
-    axis("image"); set(gca, 'YDir', 'normal');
-    colorbar; xlabel("X (m)"); ylabel("Y (m)");
-    title("Linearly Normalized SINR (dB)");
-    subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
-    addSensorOverlay(gca, sensorXY, sensorTilts, sensorAzimuths, tailScale);
-end
-
-function addSensorOverlay(ax, sensorXY, tilts, azimuths, tailScale)
-    % Draw a marker + boresight arrow for each sensor.
-    % Tail direction follows azimuth convention (0=+Y, 90=+X, clockwise).
-    % Tail length = tailScale * sind(tilt), so nadir (0°) has no tail and
-    % horizon (90°) has the full tailScale length.
-    hold(ax, 'on');
-    for ii = 1:size(sensorXY, 1)
-        x = sensorXY(ii, 1);
-        y = sensorXY(ii, 2);
-        if ii == 1
-            c = [0, 0, 0];
-            mk = 'o';
-        else
-            c = [0.9, 0.2, 0.2];
-            mk = 'x';
-        end
-        scatter(ax, x, y, 80, c, mk, LineWidth=2);
-        if tilts(ii) > 0
-            u = tailScale * sind(tilts(ii)) * sind(azimuths(ii));
-            v = tailScale * sind(tilts(ii)) * cosd(azimuths(ii));
-            quiver(ax, x, y, u, v, 0, Color=c, LineWidth=2, MaxHeadSize=1.0);
-        end
-    end
-    hold(ax, 'off');
-end

@rfSensor/rfSensor.m

@@ -1,40 +0,0 @@
-classdef rfSensor
-    properties (SetAccess = private, GetAccess = public)
-        % Physical parameters
-        c = 3e8; % Speed of light (m/s)
-        k_B = 1.38e-23 % Boltzmann constant (W/Hz/K) for thermal noise model
-        T_0 = 300; % Ambient temperature (Kelvin) for thermal noise model
-        lossExponent = NaN; % Path loss exponent (2 for free space, up to 6 for the lossiest environments)
-        % Sensor parameters
-        P_TX = NaN; % Transmit power (Watts)
-        BW = NaN; % Bandwidth (Hz)
-        f_c = NaN; % Center frequency (Hz)
-        G_RX_dBi = NaN; % Receiver antenna gain
-        beamwidthExponent = NaN; % Antenna beamwidth exponent for cosine radiation pattern, larger exponent -> narrower beam
-        % Values computed at initialization
-        P_TX_dBm = NaN; % Transmit power (dBm)
-        N = NaN; % Thermal noise
-        % Cached state (per timestep)
-    end
-    properties (Access = public)
-        tilt = NaN;     % Antenna boresight tilt (deg): 0=nadir, 90=horizon
-        azimuth = NaN;  % Antenna boresight azimuth (deg): 0=+y, 90=+x, 180=-y, 270=-x
-        rssCache (:,1) double = double.empty(0,1); % linear-scale RSS to last ground targets grid
-    end
-
-    methods (Access = public)
-        [obj] = initialize(obj, txPower, bandwidth, centerFreq, rxGain, beamwidthExponent, tilt, azimuth); % initialize sensor, define parameters
-        [SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors); % determine sensor performance for a given single sensor and target geometry
-        [d, dx, dy, dz] = computePointToPoints(obj, agentPos, targetPos);
-        [value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
-        [f] = plotParameters(obj); % debug, plot sensor response as a function of distance and tilt angle
-        [f] = plotPerformance(obj, altitude, otherSensorsPos, otherSensors); % debug, plot SNR or SINR ground heatmap for a given geometry
-        [f] = plot(obj, altitude, otherSensorsPos, otherSensors);
-        obj = clearRssCache(obj);
-    end
-    methods (Access = private)
-        x = RSS(obj, d, dx, dy, dz); % Received signal strength (function of distance and tilt angle)
-        G_TX_dB = transmitterGain(obj, t, a); % Antenna gain for a given TX/RX pair 
-        L_FSPL_dB = pathLoss(obj, d); % Free space path loss for a given TX/RX pair
-    end
-end

@rfSensor/sensorPerformance.m

@@ -1,34 +0,0 @@
-function [SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        agentPos (1, 3) double;
-        targetPos (:, 3) double;
-        otherSensorsPos (:, 3) double = [];
-        otherSensors (:, 1) cell = {};
-    end
-    arguments (Output)
-        SINR (:, 1) double;
-        SNR (:, 1) double;
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        otherSensors (:, 1) cell;
-    end
-    assert(size(otherSensorsPos, 1) == size(otherSensors, 1), "Mismatch in number of other sensor positions (%d) and number of other sensors (%d) provided", size(otherSensorsPos, 1), size(otherSensors, 1));
-
-    if isempty(obj.rssCache)
-        [d, dx, dy, dz] = obj.computePointToPoints(agentPos, targetPos);
-        obj.rssCache = 1e-3 .* 10 .^ (0.1 .* obj.RSS(d, dx, dy, dz));  % dBm → W
-    end
-    S = obj.rssCache;
-
-    I = zeros(size(S));
-    for ii = 1:size(otherSensors, 1)
-        if isempty(otherSensors{ii}.rssCache)
-            [d_o, dx_o, dy_o, dz_o] = otherSensors{ii}.computePointToPoints(otherSensorsPos(ii, 1:3), targetPos);
-            otherSensors{ii}.rssCache = 1e-3 .* 10 .^ (0.1 .* otherSensors{ii}.RSS(d_o, dx_o, dy_o, dz_o));  % dBm → W
-        end
-        I = I + otherSensors{ii}.rssCache;
-    end
-
-    SINR = 10*log10(S ./ (I + obj.N));
-    SNR  = 10*log10(S ./ obj.N);
-end

@rfSensor/transmitterGain.m

@@ -1,23 +0,0 @@
-function value = transmitterGain(obj, t, a)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "rfSensor")};
-        t (:, 1) double; % LOS tilt angle
-        a (:, 1) double; % LOS azimuth angle
-    end
-    arguments (Output)
-        value (:, 1) double
-    end
-    if ~isequal(size(t), size(a))
-        error("t and a must be the same size");
-    end
-
-    % Angular offset from boresight via spherical law of cosines
-    % Convention: t=0° nadir, t=90° horizon; a=0° +y, a=90° +x
-    cos_theta = sind(obj.tilt) .* sind(t) .* cosd(a - obj.azimuth) + ...
-                cosd(obj.tilt) .* cosd(t);
-    cos_theta = max(-1, min(1, cos_theta));  % clamp for numerical safety
-    theta = acosd(cos_theta);
-
-    % Cardioid family: peak at boresight (theta=0), null opposite (theta=180°)
-    value = 10 .* obj.beamwidthExponent .* log10((1 + cosd(theta)) ./ 2);
-end

@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

@sensingObjective/plot.m

@@ -11,26 +11,19 @@ function f = plot(obj, ind, f)
     % Create axes if they don't already exist
     f = firstPlotSetup(f);
 
-    normalized = obj.values ./ sum(obj.values, "all");
-    cRange = [min(normalized, [], "all"), max(normalized, [], "all")];
-
     % Plot gradient on the "floor" of the domain
     if isnan(ind)
-        ax = f.CurrentAxes;
+        hold(f.CurrentAxes, "on");
-        hold(ax, "on");
+        o = surf(f.CurrentAxes, obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
-        o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
         o.HitTest = "off";
         o.PickableParts = "none";
-        clim(ax, cRange);
+        hold(f.CurrentAxes, "off");
-        hold(ax, "off");
     else
-        ax = f.Children(1).Children(ind(1));
+        hold(f.Children(1).Children(ind(1)), "on");
-        hold(ax, "on");
+        o = surf(f.Children(1).Children(ind(1)), obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
-        o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
         o.HitTest = "off";
         o.PickableParts = "none";
-        clim(ax, cRange);
+        hold(f.Children(1).Children(ind(1)), "off");
-        hold(ax, "off");
     end
 
     % Add to other perspectives

@sigmoidSensor/halfAngle.m

@@ -1,9 +0,0 @@
-function value = halfAngle(obj)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, "sigmoidSensor")};
-    end
-    arguments (Output)
-        value (1, 1) double;
-    end
-    value = obj.alphaTilt;
-end

@sigmoidSensor/initialize.m

@@ -1,24 +1,17 @@
-function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth)
+function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
         alphaDist (1, 1) double;
         betaDist (1, 1) double;
         alphaTilt (1, 1) double;
         betaTilt (1, 1) double;
-        tilt (1, 1) double = 0;
-        azimuth (1, 1) double = 0;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
     end
     
-    % Sensor performance parameters
     obj.alphaDist = alphaDist;
     obj.betaDist = betaDist;
     obj.alphaTilt = alphaTilt;
     obj.betaTilt = betaTilt;
-
-    % Sensor pointing parameters
-    obj.tilt = tilt;
-    obj.azimuth = azimuth;
 end

@sigmoidSensor/sensorPerformance.m

@@ -8,20 +8,16 @@ function value = sensorPerformance(obj, agentPos, targetPos)
         value (:, 1) double;
     end
 
-    % Unit vectors from agent to each target
+    % compute direct distance and distance projected onto the ground
-    diffs = targetPos - agentPos;
+    d = vecnorm(agentPos - targetPos, 2, 2); % distance from sensor to target
-    d = vecnorm(diffs, 2, 2);
+    x = vecnorm(agentPos(1:2) - targetPos(:, 1:2), 2, 2); % distance from sensor nadir to target nadir (i.e. distance ignoring height difference)
-    dirs = diffs ./ d;
 
-    % Boresight unit vector: tilt=0 → nadir [0,0,-1]; azimuth 0=+Y, 90=+X clockwise
+    % compute tilt angle
-    boresight = [sind(obj.tilt)*sind(obj.azimuth), sind(obj.tilt)*cosd(obj.azimuth), -cosd(obj.tilt)];
+    tiltAngle = (180 - atan2d(x, targetPos(:, 3) - agentPos(3))); % degrees
-
-    % Angular offset from boresight to each target direction
-    angularOffset = acosd(dirs * boresight');
 
     % Membership functions
     mu_d = obj.distanceMembership(d);
-    mu_t = obj.tiltMembership(angularOffset);
+    mu_t = obj.tiltMembership(tiltAngle);
 
     value = mu_d .* mu_t; % assume pan membership is always 1
 end

@sigmoidSensor/sigmoidSensor.m

@@ -6,20 +6,14 @@ classdef sigmoidSensor
         alphaTilt = NaN; % degrees
         betaTilt = NaN;
     end
-    properties (Access = public)
-        % pointing states
-        tilt = 0;
-        azimuth = 0;
-    end
 
     methods (Access = public)
-        [obj]   = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth); % initialize sensor, define parameters
+        [obj]               = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt);
-        [value] = sensorPerformance(obj, agentPos, targetPos); % determine sensor performance for a given single sensor and target geometry
+        [value]             = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos);
-        [value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
+        [f] = plotParameters(obj);
-        [f]     = plotParameters(obj); % debug, plot sensor response as a function of distance and tilt angle
     end
     methods (Access = private)
-        x = distanceMembership(obj, d); % used in computing distance factor of sensor performance
+        x = distanceMembership(obj, d);
-        x = tiltMembership(obj, t); % used in computing tilt factor of sensor performance
+        x = tiltMembership(obj, t);
     end
 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, 100, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 80.0", "0.25, 0.25", "8.0, 8.0", "0.1, 0.1", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "66.6, 66.6", "55, 35, 35, 55", 0.15, "15.0, 15.0, 50.0, 40.0, 15.0, 50.0", 1, "0.0, 35.0, 0.0", "50, 40.0, 60", 1, 2.0, 1
+1, 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
-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

aerpaw/config/scenario_lock.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
-1, 65, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "65.0, 15.0, 65.0, 65.0, 15.0, 45.0", 3, "0.0, 25.0, 55.0, 40.0, 10.0, 0.0, 40.0, 45.0, 60.0", "100.0, 70.0, 60.0, 45.0, 80.0, 55.0, 100.0, 50.0, 100.0", 0, 2.0, 1

aerpaw/config/scenario_two_around_wall.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
-1, 100, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 80.0", "0.25, 0.25", "8.0, 8.0", "0.1, 0.1", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "66.6, 66.6", "55, 35, 35, 55", 0.15, "15.0, 15.0, 50.0, 40.0, 15.0, 50.0", 1, "0.0, 35.0, 0.0", "50, 40.0, 60", 1, 2.0, 1

aerpaw/config/scenario_walls.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
-1, 65, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "90.0, 10.0, 50.0, 65.0, 15.0, 45.0", 4, "0.0, 30.0, 0.0, 70.0, 30.0, 0.0, 0.0, 60.0, 0.0, 55.0, 60.0, 0.0", "50.0, 40.0, 100.0, 100.0, 40.0, 100.0, 35.0, 70.0, 100.0, 100.0, 70.0, 100.0", 0, 2.0, 1

aerpaw/controller.coderprj

@@ -138,41 +138,6 @@
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                   <Size type="coderapp.internal.codertype.Dimension"/>
                 </Types>
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-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="29" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="30" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="31" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="32" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="33" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
-                <Types id="34" type="coderapp.internal.codertype.PrimitiveType">
-                  <ClassName>int32</ClassName>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                  <Size type="coderapp.internal.codertype.Dimension"/>
-                </Types>
               </Types>
             </coderapp.internal.interface.project.Interface>
           </MF0>
@@ -414,773 +379,719 @@
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                   <File type="coderapp.internal.util.mfz.FileSpec">
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                   </File>
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                 </Artifacts>
                 <Artifacts id="42" type="coderapp.internal.build.mfz.CodegenArtifact">
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@@ -1188,7 +1099,7 @@
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aerpaw/controller.m

@@ -7,8 +7,7 @@ coder.extrinsic('disp', 'readScenarioCsv');
 
 % Maximum clients supported (one initial position per UAV)
 MAX_CLIENTS = 4;
-% Two waypoints per UAV: altitude-staggered transit + final position
+MAX_TARGETS = MAX_CLIENTS;
-MAX_TARGETS = MAX_CLIENTS * 2;
 
 % Allocate targets array (MAX_TARGETS x 3)
 targets = zeros(MAX_TARGETS, 3);
@@ -34,31 +33,8 @@ else
     numWaypoints = totalLoaded / int32(numClients);
 end
 
-% In the compiled path, inject altitude-staggered transit waypoints so UAVs
-% are vertically separated while flying horizontally to their start positions.
-% ArduPilot reaches target altitude before horizontal movement, so UAV i is at
-% altitude (TRANSIT_ALT_BASE + (i-1)*TRANSIT_ALT_STEP) throughout its transit,
-% preventing collisions regardless of horizontal path geometry.
-% TRANSIT_ALT_STEP must exceed 2 * max(collisionRadius).
-% Waypoint 1: each UAV flies to (finalX, finalY) at its unique transit altitude.
-% Waypoint 2: each UAV adjusts to its actual target altitude.
-% These constants are also used for the altitude-staggered return before RTL.
-TRANSIT_ALT_BASE = 25.0;  % must match drone.takeoff() altitude in uav_runner.py
-TRANSIT_ALT_STEP = 25;    % vertical separation per UAV (m); must exceed 2*collisionRadius
-if ~coder.target('MATLAB')
-    for ii = double(totalLoaded):-1:1
-        transitRow = (ii - 1) * 2 + 1;
-        finalRow   = (ii - 1) * 2 + 2;
-        finalPos   = targets(ii, :);
-        transitAlt = TRANSIT_ALT_BASE + (ii - 1) * TRANSIT_ALT_STEP;
-        targets(finalRow, :)   = finalPos;
-        targets(transitRow, :) = [finalPos(1), finalPos(2), transitAlt];
-    end
-    numWaypoints = int32(2);
-end
-
 % Load guidance scenario from CSV (parameters for guidance_step)
-NUM_SCENARIO_PARAMS = 55;
+NUM_SCENARIO_PARAMS = 45;
 MAX_OBSTACLES_CTRL  = int32(8);
 scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
 obstacleMin    = zeros(MAX_OBSTACLES_CTRL, 3);
@@ -102,7 +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));
@@ -149,10 +125,6 @@ guidance_step(positions(1:numClients, :), true, ...
 
 % 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);
@@ -163,7 +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
 
@@ -192,26 +164,9 @@ if ~coder.target('MATLAB')
     % last guidance navigation and is back in sequential (ACK/READY) mode.
     coder.ceval('waitForAllMessageType', int32(numClients), ...
                 int32(MESSAGE_TYPE.ACK));
-    % Reset step counter so post-guidance logging carries no step prefix.
-    coder.ceval('setGuidanceStep', int32(0), int32(MAX_GUIDANCE_STEPS));
 end
 % --------------------------------------------------------------------------
 
-% Altitude-staggered return: separate UAVs vertically before issuing RTL,
-% mirroring the initial positioning stagger so UAVs transit laterally at
-% unique altitudes and cannot collide during the return flight.
-if ~coder.target('MATLAB')
-    for i = 1:numClients
-        transitAlt = TRANSIT_ALT_BASE + (double(i) - 1) * TRANSIT_ALT_STEP;
-        target = [positions(i, 1), positions(i, 2), transitAlt];
-        coder.ceval('sendTarget', int32(i), coder.ref(target));
-    end
-    coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.ACK));
-    coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.READY));
-else
-    disp('Altitude-staggered return (simulation): UAVs commanded to transit altitudes.');
-end
-
 % Send RTL command to all clients
 for i = 1:numClients
     if coder.target('MATLAB')

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
@@ -94,34 +91,26 @@ if isInit
         BETA_TILT_VEC        = scenarioParams(29:32);
         DOMAIN_MIN                  = scenarioParams(33:35);
         DOMAIN_MAX                  = scenarioParams(36:38);
-        NUM_OBJ_COMPONENTS          = int32(scenarioParams(39));
+        OBJECTIVE_GROUND_POS        = scenarioParams(39:40);
-        OBJECTIVE_POS_FLAT          = scenarioParams(40:43); % [x1,y1,x2,y2]; zero-padded if N=1
+        OBJECTIVE_VAR               = reshape(scenarioParams(41:44), 2, 2);
-        OBJECTIVE_VAR_FLAT          = scenarioParams(44:51); % [v11,v12,v21,v22 per component]
+        SENSOR_PERFORMANCE_MINIMUM  = scenarioParams(45);
-        SENSOR_PERFORMANCE_MINIMUM  = scenarioParams(52);
-        USE_DOUBLE_INTEGRATOR       = logical(scenarioParams(53));
-        DAMPING_COEFF               = scenarioParams(54);
-        USE_FIXED_TOPOLOGY          = logical(scenarioParams(55));
 
         % --- Build domain geometry ---
         dom = rectangularPrism;
         dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
 
-        % --- Build sensing objective: sum of N bivariate Gaussians (codegen-compatible) ---
+        % --- Build sensing objective (inline Gaussian; codegen-compatible) ---
         dom.objective = sensingObjective;
         xGrid = unique([DOMAIN_MIN(1):DISCRETIZATION_STEP:DOMAIN_MAX(1), DOMAIN_MAX(1)]);
         yGrid = unique([DOMAIN_MIN(2):DISCRETIZATION_STEP:DOMAIN_MAX(2), DOMAIN_MAX(2)]);
         [gridX, gridY] = meshgrid(xGrid, yGrid);
-        objValues = zeros(size(gridX));
+        dx = gridX - OBJECTIVE_GROUND_POS(1);
-        for kk = 1:NUM_OBJ_COMPONENTS
+        dy = gridY - OBJECTIVE_GROUND_POS(2);
-            pos_k = OBJECTIVE_POS_FLAT((kk-1)*2+1 : (kk-1)*2+2);
+        % Bivariate Gaussian using objectiveVar covariance matrix (avoids inv())
-            var_k = reshape(OBJECTIVE_VAR_FLAT((kk-1)*4+1 : (kk-1)*4+4), 2, 2);
+        ov_a = OBJECTIVE_VAR(1,1); ov_b = OBJECTIVE_VAR(1,2);
-            dx = gridX - pos_k(1);
+        ov_c = OBJECTIVE_VAR(2,1); ov_d = OBJECTIVE_VAR(2,2);
-            dy = gridY - pos_k(2);
+        ov_det = ov_a * ov_d - ov_b * ov_c;
-            ov_a = var_k(1,1); ov_b = var_k(1,2);
+        objValues = exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
-            ov_c = var_k(2,1); ov_d = var_k(2,2);
-            ov_det = ov_a * ov_d - ov_b * ov_c;
-            objValues = objValues + exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
-        end
         dom.objective = dom.objective.initializeWithValues(objValues, dom, ...
             DISCRETIZATION_STEP, PROTECTED_RANGE, SENSOR_PERFORMANCE_MINIMUM);
 
@@ -157,8 +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
@@ -188,9 +176,7 @@ else
     sim.timestepIndex = sim.timestepIndex + 1;
 
     % 3. Update communications topology (Lesser Neighbour Assignment)
-    if ~sim.useFixedTopology
+    sim = sim.lesserNeighbor();
-        sim = sim.lesserNeighbor();
-    end
 
     % 4. Compute Voronoi partitioning
     sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
@@ -198,8 +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.timestepIndex, ii, sim.agents);
-                                             sim.useDoubleIntegrator, sim.dampingCoeff, sim.timestep, sim.optimizeSensorPointing);
     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() {}
@@ -222,13 +184,9 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
 //   28-31: betaTilt[1:4]
 //   32-34: domainMin  (east, north, up)
 //   35-37: domainMax  (east, north, up)
-//   38   : numObjectiveComponents (1 or 2; inferred from objectivePos field length)
+//   38-39: objectivePos (east, north)
-//   39-42: objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
+//   40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
-//   43-50: objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
+//   44   : sensorPerformanceMinimum
-//   51   : sensorPerformanceMinimum  (CSV column 18)
-//   52   : useDoubleIntegrator       (CSV column 23)
-//   53   : dampingCoeff              (CSV column 24)
-//   54   : useFixedTopology          (CSV column 25)
 // Returns 1 on success, 0 on failure.
 int loadScenario(const char* filename, double* params) {
     char line[4096];
@@ -240,8 +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;
     }
 
@@ -306,78 +264,34 @@ int loadScenario(const char* filename, double* params) {
         }
     }
 
-    // objectivePos: column 16 — 2 values per component (up to 2 components).
+    // objectivePos: column 16
-    // Infer numObjectiveComponents from the number of values parsed.
     {
         char tmp[256]; strncpy(tmp, fields[16], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
         char* t = trimField(tmp);
-        double posVals[4] = {0, 0, 0, 0};
+        if (sscanf(t, "%lf , %lf", &params[38], &params[39]) != 2) {
-        int posCount = 0;
+            fprintf(stderr, "loadScenario: failed to parse objectivePos: %s\n", t);
-        char* tok = strtok(t, ",");
-        while (tok && posCount < 4) {
-            posVals[posCount++] = atof(tok);
-            tok = strtok(nullptr, ",");
-        }
-        // Check for a 5th token — would mean > 2 components
-        if (tok) {
-            fprintf(stderr, "loadScenario: at most 2 objective Gaussian components supported (objectivePos has >4 values)\n");
             return 0;
         }
-        if (posCount == 0 || posCount % 2 != 0) {
-            fprintf(stderr, "loadScenario: objectivePos must have 2 or 4 values, got %d\n", posCount);
-            return 0;
-        }
-        int nObj = posCount / 2;
-        params[38] = (double)nObj;
-        for (int k = 0; k < 4; k++) params[39 + k] = posVals[k];  // zero-padded for nObj=1
     }
 
-    // objectiveVar: column 17 — 4 values per component (v11,v12,v21,v22).
+    // objectiveVar: column 17, format "v11, v12, v21, v22"
     {
-        char tmp[512]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
+        char tmp[256]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
         char* t = trimField(tmp);
-        int nObj = (int)params[38];
+        if (sscanf(t, "%lf , %lf , %lf , %lf", &params[40], &params[41], &params[42], &params[43]) != 4) {
-        double varVals[8] = {0, 0, 0, 0, 0, 0, 0, 0};
+            fprintf(stderr, "loadScenario: failed to parse objectiveVar: %s\n", t);
-        int varCount = 0;
-        char* tok = strtok(t, ",");
-        while (tok && varCount < 8) {
-            varVals[varCount++] = atof(tok);
-            tok = strtok(nullptr, ",");
-        }
-        if (varCount != nObj * 4) {
-            fprintf(stderr, "loadScenario: objectiveVar has %d values but expected %d (4 per component)\n",
-                    varCount, nObj * 4);
             return 0;
         }
-        for (int k = 0; k < 8; k++) params[43 + k] = varVals[k];  // zero-padded for nObj=1
     }
 
     // sensorPerformanceMinimum: column 18
     {
         char tmp[64]; strncpy(tmp, fields[18], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
-        params[51] = atof(trimField(tmp));
+        params[44] = atof(trimField(tmp));
     }
 
-    // useDoubleIntegrator: column 23
+    printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g]\n",
-    {
+           params[32], params[33], params[34], params[35], params[36], params[37]);
-        char tmp[64]; strncpy(tmp, fields[23], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
-        params[52] = atof(trimField(tmp));
-    }
-
-    // dampingCoeff: column 24
-    {
-        char tmp[64]; strncpy(tmp, fields[24], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
-        params[53] = atof(trimField(tmp));
-    }
-
-    // useFixedTopology: column 25
-    {
-        char tmp[64]; strncpy(tmp, fields[25], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
-        params[54] = atof(trimField(tmp));
-    }
-
-    printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g], %d objective component(s)\n",
-           params[32], params[33], params[34], params[35], params[36], params[37], (int)params[38]);
     return 1;
 }
 
@@ -516,22 +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;
 }
 
@@ -550,7 +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;
 }
@@ -598,36 +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;
 }
 
@@ -662,7 +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

@@ -27,14 +27,10 @@ int loadTargets(const char* filename, double* targets, int maxClients);
 //   28-31 betaTilt[1:4]
 //   32-34 domainMin
 //   35-37 domainMax
-//   38    numObjectiveComponents (1 or 2; inferred from objectivePos field length)
+//   38-39 objectivePos
-//   39-42 objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
+//   40-43 objectiveVar (2x2 col-major)
-//   43-50 objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
+//   44    sensorPerformanceMinimum
-//   51    sensorPerformanceMinimum
+#define NUM_SCENARIO_PARAMS 45
-//   52    useDoubleIntegrator  (0=single-integrator, 1=double-integrator)
-//   53    dampingCoeff
-//   54    useFixedTopology     (0=dynamic lesser-neighbor, 1=fixed)
-#define NUM_SCENARIO_PARAMS 55
 #define MAX_CLIENTS_PER_PARAM 4
 // Maximum number of obstacles (upper bound for pre-allocated arrays).
 #define MAX_OBSTACLES 8
@@ -63,7 +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/controllerAnalysis.m

@@ -1,28 +0,0 @@
-function controller = controllerAnalysis(resultsPath)
-    arguments (Input)
-        resultsPath (1, 1) string;
-    end
-    arguments (Output)
-        controller table;
-    end
-    
-    % Measure intervals between issuing commands from the controller 
-    % (make sure this is ~4-5 seconds at minimum to avoid overwhelming the UAV autopilot)
-    r = dir(resultsPath);
-    controllerPath = fullfile(r(startsWith({r.name}, 'controller_')).folder, r(startsWith({r.name}, 'controller_')).name);
-    controllerPath = dir(controllerPath);
-    controllerPath = fullfile(controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).folder, controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).name);
-    controller = readControllerLogs(controllerPath);
-    rpIdx = startsWith(controller.message, "Iteration duration: ");
-    s = split(controller.message(rpIdx), "Iteration duration: ");
-    s = split(s(:, 2), ' s');
-    s = duration(strcat("00:", s(:, 1)), "InputFormat", "mm:ss.SSS");
-    s.Format = "mm:ss.SSS";
-    fprintf("Minimum command spacing: %2.3f seconds\n", seconds(min(s)));
-    fprintf("Maximum command spacing: %2.3f seconds\n", seconds(max(s)));
-    fprintf("Mean command spacing: %2.3f seconds\n", seconds(mean(s)));
-    fprintf("Median command spacing: %2.3f seconds\n", seconds(median(s)));
-    if seconds(min(s)) < 4 
-        warning("Minimum command spacing %2.3f questionably short for AERPAW", seconds(min(s)));
-    end
-end

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/plotRadioLogs.m

@@ -1,12 +1,9 @@
-function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
+function [f, R] = plotRadioLogs(resultsPath)
     arguments (Input)
         resultsPath (1, 1) string;
-        G cell = {};
-        tLim (1, 2) datetime = [datetime(-Inf, 'ConvertFrom', 'datenum'), datetime(Inf, 'ConvertFrom', 'datenum')];
     end
     arguments (Output)
         f (1, 1) matlab.ui.Figure;
-        fDist (1, 1) matlab.ui.Figure;
         R cell;
     end
 
@@ -43,44 +40,11 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
 
     metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
     yLabels     = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
-    nMetrics    = numel(metricNames);
 
-    % --- Time-based figure ---
     f = figure;
-    tl = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
+    tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
 
-    % Distance vs time tile (first)
+    for mi = 1:numel(metricNames)
-    ax = nexttile(tl);
-    hold(ax, 'on'); grid(ax, 'on');
-    legendEntries = string.empty;
-    ci = 1;
-    if ~isempty(G)
-        for rxIdx = 1:nUAV
-            tbl = R{rxIdx};
-            txIDs = unique(tbl.TxUAVID);
-            for ti = 1:numel(txIDs)
-                txID = txIDs(ti);
-                rows = tbl(tbl.TxUAVID == txID, :);
-                rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
-                if isempty(rows), continue; end
-                [~, ia] = unique(rows.Timestamp);
-                [radioPt, dist] = pairDist(rows(ia, :), G);
-                if isempty(dist) || all(isnan(dist)), continue; end
-                valid = ~isnan(dist);
-                si = mod(ci - 1, numel(styles)) + 1;
-                plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
-                    styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
-                legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
-                ci = ci + 1;
-            end
-        end
-    end
-    ylabel(ax, 'Distance (m)');
-    xlabel(ax, 'Time');
-    legend(ax, legendEntries, 'Location', 'best');
-    hold(ax, 'off');
-
-    for mi = 1:nMetrics
         ax = nexttile(tl);
         hold(ax, 'on');
         grid(ax, 'on');
@@ -93,32 +57,23 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
             for ti = 1:numel(txIDs)
                 txID = txIDs(ti);
                 rows = tbl(tbl.TxUAVID == txID, :);
-                rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
                 vals = rows.(metricNames(mi));
-                valid = ~isnan(vals);
-                rows = rows(valid, :);
-                vals = vals(valid);
 
-                if isempty(rows)
+                % Skip if all NaN for this metric
+                if all(isnan(vals))
                     continue;
                 end
 
                 si = mod(ci - 1, numel(styles)) + 1;
                 plot(ax, rows.Timestamp, vals, styles(si), ...
-                    'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
+                    'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
                 legendEntries(end+1) = sprintf("TX %d → RX %d", txID, tbl.RxUAVID(1)); %#ok<AGROW>
-
-                % Median per 1/3-second time bin
-                [t_med, v_med] = timeBinMedian(posixtime(rows.Timestamp), vals, 1/3);
-                plot(ax, datetime(t_med, 'ConvertFrom', 'posixtime'), v_med, '-', ...
-                    'Color', 'r', 'LineWidth', 2);
-                legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, tbl.RxUAVID(1)); %#ok<AGROW>
                 ci = ci + 1;
             end
         end
 
         ylabel(ax, yLabels(mi));
-        if mi == nMetrics
+        if mi == numel(metricNames)
             xlabel(ax, 'Time');
         end
         legend(ax, legendEntries, 'Location', 'best');
@@ -126,134 +81,4 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
     end
 
     title(tl, 'Radio Channel Metrics');
-
-    % --- Distance-based figure ---
-    fDist = figure;
-
-    if isempty(G)
-        return;
-    end
-
-    tl2 = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
-
-    % Distance vs time tile (first)
-    ax = nexttile(tl2);
-    hold(ax, 'on'); grid(ax, 'on');
-    legendEntries = string.empty;
-    ci = 1;
-    for rxIdx = 1:nUAV
-        tbl = R{rxIdx};
-        txIDs = unique(tbl.TxUAVID);
-        for ti = 1:numel(txIDs)
-            txID = txIDs(ti);
-            rows = tbl(tbl.TxUAVID == txID, :);
-            rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
-            if isempty(rows), continue; end
-            [~, ia] = unique(rows.Timestamp);
-            [radioPt, dist] = pairDist(rows(ia, :), G);
-            if isempty(dist) || all(isnan(dist)), continue; end
-            valid = ~isnan(dist);
-            si = mod(ci - 1, numel(styles)) + 1;
-            plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
-                styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
-            legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
-            ci = ci + 1;
-        end
-    end
-    ylabel(ax, 'Distance (m)');
-    xlabel(ax, 'Time');
-    legend(ax, legendEntries, 'Location', 'best');
-    hold(ax, 'off');
-
-    for mi = 1:nMetrics
-        ax = nexttile(tl2);
-        hold(ax, 'on');
-        grid(ax, 'on');
-
-        legendEntries = string.empty;
-        ci = 1;
-        for rxIdx = 1:nUAV
-            tbl = R{rxIdx};
-            txIDs = unique(tbl.TxUAVID);
-            for ti = 1:numel(txIDs)
-                txID = txIDs(ti);
-                rows = tbl(tbl.TxUAVID == txID, :);
-
-                if isempty(rows)
-                    continue;
-                end
-
-                rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
-                if isempty(rows)
-                    continue;
-                end
-
-                vals = rows.(metricNames(mi));
-                valid = ~isnan(vals);
-                rows = rows(valid, :);
-                vals = vals(valid);
-
-                if isempty(rows)
-                    continue;
-                end
-
-                [radioPt, dist] = pairDist(rows, G);
-                if isempty(dist) || all(isnan(dist)), continue; end
-
-                % Drop points where GPS interpolation returned NaN
-                validDist = ~isnan(dist);
-                rowTs = radioPt(validDist);
-                dist  = dist(validDist);
-                vals  = vals(validDist);
-
-                si = mod(ci - 1, numel(styles)) + 1;
-                scatter(ax, dist, vals, 9, colors(ci, :), strrep(styles(si), "-", ""), 'filled');
-                legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
-
-                % Median per 1/3-second time bin, plotted against median distance
-                [~, dv_med] = timeBinMedian(rowTs, [dist, vals], 1/3);
-                [d_med, si_sort] = sort(dv_med(:, 1));
-                v_med = dv_med(si_sort, 2);
-                plot(ax, d_med, v_med, '-', 'Color', 'r', 'LineWidth', 2);
-                legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, rows.RxUAVID(1)); %#ok<AGROW>
-                ci = ci + 1;
-            end
-        end
-
-        ylabel(ax, yLabels(mi));
-        if mi == nMetrics
-            xlabel(ax, 'Distance (m)');
-        end
-        legend(ax, legendEntries, 'Location', 'best');
-        hold(ax, 'off');
-    end
-
-    title(tl2, 'Radio Channel Metrics vs Distance');
-end
-
-
-function [radioPt, dist] = pairDist(rows, G)
-    % Interpolate GPS-based inter-UAV distance at each row's timestamp.
-    radioPt = []; dist = [];
-    txGpsIdx = double(rows.TxUAVID(1)) + 1;
-    rxGpsIdx = double(rows.RxUAVID(1)) + 1;
-    if txGpsIdx > numel(G) || rxGpsIdx > numel(G), return; end
-    Gtx = G{txGpsIdx};
-    Grx = G{rxGpsIdx};
-    if ~ismember('East', Gtx.Properties.VariableNames) || ...
-       ~ismember('East', Grx.Properties.VariableNames), return; end
-    txTs = Gtx.Timestamp; txTs.TimeZone = '';
-    rxTs = Grx.Timestamp; rxTs.TimeZone = '';
-    txPt = posixtime(txTs);
-    rxPt = posixtime(rxTs);
-    radioPt = posixtime(rows.Timestamp);
-    validTx = ~isnan(Gtx.East);
-    validRx = ~isnan(Grx.East);
-    txE = interp1(txPt(validTx), Gtx.East(validTx),  radioPt, 'linear', NaN);
-    txN = interp1(txPt(validTx), Gtx.North(validTx), radioPt, 'linear', NaN);
-    txU = interp1(txPt(validTx), Gtx.Up(validTx),    radioPt, 'linear', NaN);
-    rxE = interp1(rxPt(validRx), Grx.East(validRx),  radioPt, 'linear', NaN);
-    rxN = interp1(rxPt(validRx), Grx.North(validRx), radioPt, 'linear', NaN);
-    rxU = interp1(rxPt(validRx), Grx.Up(validRx),    radioPt, 'linear', NaN);
-    dist = vecnorm([txE - rxE, txN - rxN, txU - rxU], 2, 2);
 end

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};
 
@@ -70,40 +59,6 @@ function R = readRadioLogs(logPath)
 
     R = sortrows(R, "Timestamp");
 
-    % Reconstruct per-measurement timestamps within GNURadio processing batches.
-    % The flowgraph accumulates one full PN sequence (4095 chips at samp_rate/sps)
-    % per measurement, but outputs the whole batch simultaneously with a single
-    % wall-clock timestamp. We reassign timestamps by counting backward from the
-    % batch processing time at the known PN period interval.
-    pn_period = 4095 / (2e6 / 16);  % 32.76 ms per PN correlation period
-
-    for txId = unique(R.TxUAVID)'
-        rows = find(R.TxUAVID == txId);
-        if numel(rows) < 2, continue; end
-
-        dt = seconds(diff(R.Timestamp(rows)));
-        break_pos = [1; find(dt > 0.5) + 1];
-        end_pos   = [break_pos(2:end) - 1; numel(rows)];
-
-        for b = 1:numel(break_pos)
-            idx      = rows(break_pos(b) : end_pos(b));
-            batch_ts = posixtime(R.Timestamp(idx));
-            t_ref    = max(batch_ts);
-
-            % Multiple metric files share the same processing timestamp for
-            % each PN period, so group by unique original timestamp rather
-            % than treating every row as a separate PN period.
-            [~, ~, group_id] = unique(batch_ts);
-            n_groups = max(group_id);
-            new_ts   = t_ref - (n_groups - 1 : -1 : 0)' * pn_period;
-
-            for g = 1:n_groups
-                R.Timestamp(idx(group_id == g)) = ...
-                    datetime(new_ts(g), 'ConvertFrom', 'posixtime');
-            end
-        end
-    end
-
     % Remove rows during defined guard period between TDM shifts
     R(R.TxUAVID == -1, :) = [];
 

aerpaw/results/resultsAnalysis.m

@@ -1,16 +1,12 @@
 %% Plot AERPAW logs (trajectory, radio)
 resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % Define path to results copied from AERPAW platform
 
-% Check timeline in controller logs
-controller = controllerAnalysis(resultsPath);
-
 % 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 (time-based and distance-based)
+% Plot radio statistics
-[fRadio, fRadioDist, R] = plotRadioLogs(resultsPath, G, controller.timestamp([1, end]));
+[fRadio, R] = plotRadioLogs(resultsPath);
 
 %% Run simulation
 % Run miSim using same AERPAW scenario definition CSV
@@ -25,7 +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)
@@ -37,7 +33,7 @@ for ii = 1:size(agents, 1)
     collisionGeometry = spherical;
     collisionGeometry = collisionGeometry.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), params.collisionRadius(ii), REGION_TYPE.COLLISION, sprintf("Agent %d collision geometry", ii));
 
-    agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, 5.0, sprintf("Agent %d", ii), plotCommsGeometry);
+    agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, sprintf("Agent %d", ii), plotCommsGeometry);
 end
 
 % Create obstacles
@@ -64,12 +60,9 @@ copyobj(sim.f.Children, comparison);
 
 % Plot trajectories on top
 for ii = 1:size(G, 1)
-    gpsTimes = G{ii}.Timestamp;
-    gpsTimes.TimeZone = '';
-    inRange = gpsTimes >= controller.timestamp(1) & gpsTimes <= controller.timestamp(end);
     for jj = 1:size(sim.spatialPlotIndices, 2)
         hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "on");
-        plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East(inRange), G{ii}.North(inRange), G{ii}.Up(inRange) + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
+        plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East, G{ii}.North, G{ii}.Up + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
         hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "off");
     end
 end

aerpaw/results/timeBinMedian.m

@@ -1,29 +0,0 @@
-function [t_med, v_med] = timeBinMedian(t, v, binWidth)
-    % Compute median of each column of v within fixed-width time bins.
-    %
-    %   t        - (N,1) posixtime values
-    %   v        - (N,K) data matrix; one column per quantity
-    %   binWidth - scalar bin width in seconds
-    %
-    %   t_med    - (B,1) median time of each non-empty bin
-    %   v_med    - (B,K) median of each column per non-empty bin
-
-    edges = (floor(min(t) / binWidth) * binWidth) : binWidth : ...
-            (floor(max(t) / binWidth) * binWidth + binWidth);
-    bins  = discretize(t, edges);
-    nBins = numel(edges) - 1;
-    K     = size(v, 2);
-
-    t_all = NaN(nBins, 1);
-    v_all = NaN(nBins, K);
-    for bi = 1:nBins
-        mask = bins == bi;
-        if ~any(mask), continue; end
-        t_all(bi)   = median(t(mask));
-        v_all(bi,:) = median(v(mask,:), 1);
-    end
-
-    ok    = ~isnan(t_all);
-    t_med = t_all(ok);
-    v_med = v_all(ok, :);
-end

geometries/@cone/cone.m

@@ -6,11 +6,9 @@ classdef cone
         label = "";
 
         % Spatial
-        center  = NaN;
+        center = NaN;
-        radius  = NaN;
+        radius = NaN;
-        height  = NaN;
+        height = NaN;
-        tilt    = 0;   % degrees, 0=nadir 90=horizon
-        azimuth = 0;   % degrees, 0=+Y 90=+X clockwise
 
         % Plotting
         surface;

geometries/@cone/initialize.m

@@ -1,23 +1,19 @@
-function obj = initialize(obj, center, radius, height, tag, label, tilt, azimuth)
+function obj = initialize(obj, center, radius, height, tag, label)
     arguments (Input)
-        obj     (1, 1) {mustBeA(obj, "cone")};
+        obj (1, 1) {mustBeA(obj, "cone")};
-        center  (1, 3) double;
+        center (1, 3) double;
-        radius  (1, 1) double;
+        radius (1, 1) double;
-        height  (1, 1) double;
+        height (1, 1) double;
-        tag     (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
+        tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
-        label   (1, 1) string      = "";
+        label (1, 1) string = "";
-        tilt    (1, 1) double      = 0;
-        azimuth (1, 1) double      = 0;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "cone")};
     end
 
-    obj.center  = center;
+    obj.center = center;
-    obj.radius  = radius;
+    obj.radius = radius;
-    obj.height  = height;
+    obj.height = height;
-    obj.tag     = tag;
+    obj.tag = tag;
-    obj.label   = label;
+    obj.label = label;
-    obj.tilt    = tilt;
-    obj.azimuth = azimuth;
 end

geometries/@cone/plot.m

@@ -21,17 +21,6 @@ function [obj, f] = plot(obj, ind, f, maxAlt)
     % Scale to match height
     Z = Z * maxAlt;
     
-    % Rotate mesh around apex to match boresight tilt and azimuth.
-    % Apex sits at [0, 0, maxAlt] before center translation.
-    % Convention: tilt 0=nadir, 90=horizon; azimuth 0=+Y, 90=+X, clockwise.
-    Ry = [cosd(obj.tilt), 0, -sind(obj.tilt); 0, 1, 0; sind(obj.tilt), 0, cosd(obj.tilt)];
-    Rz = [sind(obj.azimuth), -cosd(obj.azimuth), 0; cosd(obj.azimuth), sind(obj.azimuth), 0; 0, 0, 1];
-    R  = Rz * Ry;
-    pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
-    X = reshape(pts(1, :), size(X));
-    Y = reshape(pts(2, :), size(Y));
-    Z = reshape(pts(3, :) + maxAlt, size(Z));
-
     % Move to center location
     X = X + obj.center(1);
     Y = Y + obj.center(2);

plot_1.m

@@ -0,0 +1,189 @@
+clear;
+% Load data
+dataPath = fullfile('.', 'sandbox', 'plot1');
+simHists = dir(dataPath); simHists = simHists(3:end);
+simInits = simHists(endsWith({simHists.name}, 'miSimInits.mat'));
+simHists = simHists(endsWith({simHists.name}, 'miSimHist.mat'));
+assert(length(simHists) == length(simInits), "input data availability mismatch");
+
+% Initialize plotting data
+nRuns = length(simHists);
+Cfinal = NaN(nRuns, 1);
+n = NaN(nRuns, 1);
+doubleIntegrator = NaN(nRuns, 1);
+numObjective = NaN(nRuns, 1);
+positions = cell(6, nRuns);
+commsRadius = NaN(nRuns, 1);
+collisionRadius = NaN(nRuns, 1);
+
+% Aggregate relevant data
+for ii = 1:length(simHists)
+    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));
+
+    % Stash relevant data
+    Cfinal(ii) = hist.out.perf(end) / init.objectiveIntegral;
+    n(ii) = init.numAgents;
+    doubleIntegrator(ii) = init.useDoubleIntegrator;
+    numObjective(ii) = size(init.objectivePos, 1);
+    commsRadius(ii) = unique(init.comRange);
+    collisionRadius(ii) = unique(init.collisionRadius);
+    for jj = 1:length(hist.out.agent)
+        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
+
+    alphaDist2 = unique(alphaDist);
+    if length(alphaDist2) > 1
+        alphaDist2 = alphaDist2(1);
+    end
+    if doubleIntegrator(ii) && all(alphaDist(1:n(ii), ii) == alphaDist2) && numObjective(ii) == 1
+        a2betaIdx = ii;
+        a2beta = struct("init", init, "hist", hist.out);
+    end
+end
+
+commsRadius = unique(commsRadius); assert(isscalar(commsRadius));
+collisionRadius = unique(collisionRadius); assert(isscalar(collisionRadius));
+sensors = flip(unique(alphaDist(1, :)));
+n_unique = sort(unique(n));
+nGroups = length(n_unique);
+
+% Build config label for each run
+config = strings(nRuns, 1);
+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) == sensors(1)
+        s = s + "_I";
+    elseif alphaDist(1, ii) == sensors(2)
+        s = s + "_II";
+    end
+    if ~doubleIntegrator(ii)
+        s = s + "_alpha";
+    else
+        s = s + "_beta";
+    end
+    baseConfig(ii) = s;
+    config(ii) = n(ii) + "_" + s;
+end
+configOrder = unique(baseConfig(n == n_unique(1)), 'stable');
+nConfigsPerN = length(configOrder);
+
+%%
+close all;
+f1 = figure;
+x1 = axes;
+
+C_mean = NaN(nGroups, nConfigsPerN);
+C_var = NaN(nGroups, nConfigsPerN);
+for ii = 1:nGroups
+    for jj = 1:nConfigsPerN
+        mask = (n == n_unique(ii)) & (baseConfig == configOrder(jj));
+        C_mean(ii, jj) = mean(Cfinal(mask));
+        C_var(ii, jj) = var(Cfinal(mask));
+    end
+end
+
+hBar = bar(x1, C_mean);
+hold(x1, 'on');
+for jj = 1:nConfigsPerN
+    xPos = hBar(jj).XEndPoints;
+    errorbar(x1, xPos, C_mean(:, jj), C_var(:, jj), 'k.', 'LineWidth', 1, 'HandleVisibility', 'off');  % disabled the error bars because they are small to the point of meaninglessness
+end
+hold(x1, 'off');
+set(x1, 'XTickLabel', string(n_unique));
+xlabel("Number of agents");
+ylabel("Final coverage (normalized)");
+title("Final performance of parameterizations");
+legend(["$AI\alpha$"; "$AI\beta$"; "$AII\alpha$"; "$BI\beta$"], "Interpreter", "latex", "Location", "northwest");
+grid("on");
+ylim([0, 1/2]);
+
+savefig(f1, "plot1.fig");
+exportgraphics(f1, "plot1.png");
+
+%%
+f2 = figure;
+x2 = axes;
+
+% Compute pairwise distances between agents
+maxPairs = nchoosek(6, 2);
+pairDist = cell(maxPairs, nRuns);
+for ii = 1:nRuns
+    pp = 0;
+    for jj = 1:n(ii)-1
+        for kk = jj+1:n(ii)
+            pp = pp + 1;
+            pairDist{pp, ii} = vecnorm(positions{jj, ii} - positions{kk, ii}, 2, 2);
+        end
+    end
+end
+
+% Cap pairwise distances at communications range
+for ii = 1:nRuns
+    nPairs = nchoosek(n(ii), 2);
+    for pp = 1:nPairs
+        pairDist{pp, ii} = min(pairDist{pp, ii}, commsRadius);
+    end
+end
+
+% Compute mean, min, max pairwise distance across all pairs and timesteps per run
+meanPairDist = NaN(nRuns, 1);
+minPairDist = NaN(nRuns, 1);
+maxPairDist = NaN(nRuns, 1);
+for ii = 1:nRuns
+    nPairs = nchoosek(n(ii), 2);
+    D = vertcat(pairDist{1:nPairs, ii});
+    meanPairDist(ii) = mean(D);
+    minPairDist(ii) = min(D);
+    maxPairDist(ii) = max(D);
+end
+
+% Group pairwise distance stats by (n, config), aggregating across reps
+meanD = NaN(nGroups, nConfigsPerN);
+minD = NaN(nGroups, nConfigsPerN);
+maxD = NaN(nGroups, nConfigsPerN);
+for ii = 1:nGroups
+    for jj = 1:nConfigsPerN
+        mask = (n == n_unique(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 / nConfigsPerN;
+hold(x2, 'on');
+for jj = 1:nConfigsPerN
+    xPos = (1:nGroups) + (jj - (nConfigsPerN + 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(n_unique));
+xlabel(x2, "Number of agents");
+ylabel(x2, "Pairwise distance");
+title(x2, "Pairwise Agent Distances (min/mean/max)");
+legend(x2, ["$AI\alpha$"; "$AI\beta$"; "$AII\alpha$"; "$BI\beta$"], "Interpreter", "latex");
+grid(x2, "on");
+
+yline(collisionRadius, 'r--', "Label", "Collision Radius", "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+yline(commsRadius, 'r--', "Label", "Communications Radius", "LabelHorizontalAlignment", "left", "HandleVisibility", "off");
+ylim([0, commsRadius + 5]);
+
+savefig(f2, "plot2.fig");
+exportgraphics(f2, "plot2.png");

plot_3.m

@@ -0,0 +1,142 @@
+clear;
+% Load data
+dataPath = fullfile('.', 'sandbox', 'plot3');
+simHists = dir(dataPath); simHists = simHists(3:end);
+simInits = simHists(endsWith({simHists.name}, 'miSimInits.mat'));
+simHists = simHists(endsWith({simHists.name}, 'miSimHist.mat'));
+assert(length(simHists) == length(simInits), "input data availability mismatch");
+assert(isscalar(simHists));
+
+init = fullfile(simInits(1).folder, simInits(1).name);
+hist = fullfile(simHists(1).folder, simHists(1).name);
+
+init = load(init);
+hist = load(hist);
+hist = hist.out;
+
+f3 = figure;
+x3 = axes;
+assert(size(init.objectivePos, 1) == 1)
+assert(hist.useDoubleIntegrator);
+
+plot(hist.perf./init.objectiveIntegral, "LineWidth", 2);
+hold("on");
+for ii = 1:length(hist.agent)
+    plot(hist.agent(ii).perf./init.objectiveIntegral, "LineWidth", 2);
+end
+grid("on");
+ylabel("Performance (normalized)");
+xlabel("Timestep");
+legend(["Cumulative"; "Agent 1"; "Agent 2"; "Agent 3"; "Agent 4"], "Location", "northwest");
+title("$AII\beta$ Performance", "Interpreter", "latex");
+
+savefig(f3, "plot3.fig");
+exportgraphics(f3, "plot3.png");
+
+f4 = figure;
+x4 = axes;
+
+% Compute pairwise distances between agents over time
+nAgents = length(hist.agent);
+commsRadius = hist.agent(1).commsRadius;
+collisionRadius = hist.agent(1).collisionRadius;
+nPairs = nchoosek(nAgents, 2);
+T = size(hist.agent(1).pos, 1);
+pairDistMat = NaN(T, nPairs);
+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);
+    end
+end
+
+% Cap at communications range
+% pairDistMat = min(pairDistMat, commsRadius);
+
+% Plot all pairwise distances over time
+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");
+ylim(x4, [0, commsRadius + 5]);
+
+% Build legend labels
+pairLabels = strings(nPairs, 1);
+pp = 0;
+for jj = 1:nAgents-1
+    for kk = jj+1:nAgents
+        pp = pp + 1;
+        pairLabels(pp) = sprintf("Agents %d-%d Distance", jj, kk);
+    end
+end
+
+l = legend(hLeft(:), pairLabels(:), "Location", "northeast");
+
+savefig(f4, "plot4_distanceOnly.fig");
+exportgraphics(f4, "plot4_distanceOnly.png");
+
+% Plot all barrier function values on right Y-axis
+nObs = init.numObstacles;
+nAA = nchoosek(nAgents, 2);
+nAO = nAgents * nObs;
+nAD = nAgents * 6;
+nComms = size(hist.barriers, 1) - nAA - nAO - nAD;
+
+yyaxis(x4, 'right');
+hold(x4, 'on');
+
+% Color palettes: pairs share colors across collision/comms,
+% agents share colors across obstacle/domain
+pairColors = lines(nAA);
+agentColors = lines(nAgents);
+
+% Row offsets in hist.barriers
+colStart = 1;
+obsStart = colStart + nAA;
+domStart = obsStart + nAO;
+comStart = domStart + nAD;
+
+% Collision + Comms barriers grouped per pair (same color)
+hRight = gobjects(0, 1);
+rightLabels = strings(0, 1);
+for pp = 1:nAA
+    hRight(end+1) = plot(x4, hist.barriers(colStart + pp - 1, :), '--', 'LineWidth', 1.5, 'Color', pairColors(pp, :));
+    rightLabels(end+1) = sprintf('h_{col} %d', pp);
+end
+for pp = 1:nComms
+    hRight(end+1) = plot(x4, hist.barriers(comStart + pp - 1, :), '-.', 'LineWidth', 1.5, 'Color', pairColors(pp, :));
+    rightLabels(end+1) = sprintf('h_{com} %d', pp);
+end
+
+% Obstacle barriers — colored by agent
+% idx = obsStart;
+% for aa = 1:nAgents
+%     for oo = 1:nObs
+%         hRight(end+1) = plot(x4, hist.barriers(idx, :), ':', 'LineWidth', 1, 'Color', agentColors(aa, :));
+%         rightLabels(end+1) = sprintf('h_{obs} a%d-o%d', aa, oo);
+%         idx = idx + 1;
+%     end
+% end
+
+hold(x4, 'off');
+ylabel(x4, "Barrier function $h$", "Interpreter", "latex");
+
+% Clamp both Y-axes to start at 0
+yyaxis(x4, 'left');  ylim(x4, [0, 25]);
+yyaxis(x4, 'right'); ylim(x4, [0, 275]);
+x4.YAxis(2).Color = 'k';
+
+% Combined legend
+l = legend([hLeft(:); hRight(:)], [pairLabels(:); rightLabels(:)], "Location", "eastoutside");
+
+savefig(f4, "plot4.fig");
+exportgraphics(f4, "plot4.png");

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