plot script fixes

.gitignore

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

.gitmodules

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

@agent/agent.m

@@ -6,8 +6,6 @@ classdef agent
         % State
         lastPos = NaN(1, 3); % position from previous timestep
         pos = NaN(1, 3); % current position
-        vel = zeros(1, 3); % velocity (double-integrator mode)
-        lastVel = zeros(1, 3); % pre-step velocity (double-integrator mode)
 
         % Sensor
         sensorModel;

@agent/initialize.m

@@ -15,9 +15,6 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
     end
 
     obj.pos = pos;
-    obj.lastPos = pos;
-    obj.vel = zeros(1, 3);
-    obj.lastVel = zeros(1, 3);
     obj.collisionGeometry = collisionGeometry;
     obj.sensorModel = sensorModel;
     obj.label = label;

@agent/run.m

@@ -1,4 +1,4 @@
-function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useDoubleIntegrator, dampingCoeff, dt)
+function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         domain (1, 1) {mustBeGeometry};
@@ -6,21 +6,11 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
         timestepIndex (1, 1) double;
         index (1, 1) double;
         agents (:, 1) {mustBeA(agents, "cell")};
-        useDoubleIntegrator (1, 1) logical = false;
-        dampingCoeff (1, 1) double = 2.0;
-        dt (1, 1) double = 1.0;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "agent")};
     end
 
-    % Always update lastPos/lastVel so constrainMotion evaluates barriers at
-    % the correct (most recent) position, even when this agent has no partition.
-    obj.lastPos = obj.pos;
-    if useDoubleIntegrator
-        obj.lastVel = obj.vel;
-    end
-
     % Collect objective function values across partition
     partitionMask = partitioning == index;
     if ~any(partitionMask(:))
@@ -85,25 +75,20 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
     targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
     gradNorm = norm(gradC);
 
-    % Compute unconstrained next state
-    if useDoubleIntegrator
-        % Double-integrator: gradient produces desired acceleration with damping
+    % Compute unconstrained next position.
+    % Guard against near-zero gradient: when sensor performance is saturated
+    % or near-zero across the whole partition, rateFactor -> Inf and pNext
+    % explodes. Stay put instead.
     if gradNorm < 1e-100
-            a_gradient = zeros(1, 3);
+        pNext = obj.pos;
     else
-            % Scale so steady-state step ≈ targetRate (matching SI behavior)
-            a_gradient = (targetRate * dampingCoeff / (gradNorm * dt)) * gradC;
-        end
-        % Semi-implicit Euler: unconditionally stable for any dampingCoeff and dt
-        obj.vel = (obj.vel + a_gradient * dt) / (1 + dampingCoeff * dt);
-        obj.pos = obj.lastPos + obj.vel * dt;
-    else
-        % Single-integrator: gradient directly sets position step
-        if gradNorm >= 1e-100
-            obj.pos = obj.pos + (targetRate / gradNorm) * gradC;
-        end
+        pNext = obj.pos + (targetRate / gradNorm) * gradC;
     end
 
+    % Move to next position
+    obj.lastPos = obj.pos;
+    obj.pos = pNext;
+
     % Reinitialize collision geometry in the new position
     d = obj.pos - obj.collisionGeometry.center;
     if isa(obj.collisionGeometry, "rectangularPrism")

@miSim/constrainMotion.m

@@ -8,41 +8,41 @@ function [obj] = constrainMotion(obj)
 
     nAgents = size(obj.agents, 1);
 
-    % Compute current velocity and desired control input
-    v = zeros(nAgents, 3);        % current velocity (for drift term in DI mode)
-    u_desired = zeros(nAgents, 3); % desired control: velocity (SI) or acceleration (DI)
-    for ii = 1:nAgents
-        if obj.useDoubleIntegrator
-            v(ii, :) = obj.agents{ii}.lastVel;
-            u_desired(ii, :) = (obj.agents{ii}.vel - obj.agents{ii}.lastVel) / obj.timestep;
+    if nAgents < 2
+        nAAPairs = 0;
     else
+        nAAPairs = nchoosek(nAgents, 2); % unique agent/agent pairs
+    end
+
+    % Compute velocity matrix from unconstrained gradient-ascent step
+    v = zeros(nAgents, 3);
+    for ii = 1:nAgents
         v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
-            u_desired(ii, :) = v(ii, :);
     end
-    end
-    if ~obj.useDoubleIntegrator && (all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all"))
-        % Single-integrator: agents are not attempting to move
-        return;
-    end
-    if obj.useDoubleIntegrator && all(u_desired == 0, "all") && all(v == 0, "all")
-        % Double-integrator: no desired acceleration and no existing velocity
+    if all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all")
+        % Agents are not attempting to move, so there is no motion to be
+        % constrained
         return;
     end
 
     % Initialize QP based on number of agents and obstacles
+    nAOPairs = nAgents * size(obj.obstacles, 1); % unique agent/obstacle pairs
+    nADPairs = nAgents * 6; % agents x (4 walls + 1 floor + 1 ceiling)
+    nLNAPairs = sum(obj.constraintAdjacencyMatrix, "all") - nAgents;
+    total = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
     kk = 1;
-    A = zeros(obj.numBarriers, 3 * nAgents);
-    b = zeros(obj.numBarriers, 1);
+    A = zeros(total, 3 * nAgents);
+    b = zeros(total, 1);
 
     % Set up collision avoidance constraints
     h = NaN(nAgents, nAgents);
     h(logical(eye(nAgents))) = 0; % self value is 0
     for ii = 1:(nAgents - 1)
         for jj = (ii + 1):nAgents
-            h(ii, jj) = norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
+            h(ii, jj) = norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
             h(jj, ii) = h(ii, jj);
 
-            A(kk, (3 * ii - 2):(3 * ii)) =  -2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
+            A(kk, (3 * ii - 2):(3 * ii)) =  -2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
             A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
             % Slack derived from existing params: recovery velocity = max gradient approach velocity.
             % Correction splits between 2 agents, so |A| = 2*r_sum
@@ -60,20 +60,16 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    idx = length(h(triu(true(size(h)), 1)));
-    obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
-    idx = idx + 1;
-
     hObs = NaN(nAgents, size(obj.obstacles, 1));
     % Set up obstacle avoidance constraints
     for ii = 1:nAgents
         for jj = 1:size(obj.obstacles, 1)
             % find closest position to agent on/in obstacle
-            cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.lastPos);
+            cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.pos);
 
-            hObs(ii, jj) = dot(obj.agents{ii}.lastPos - cPos, obj.agents{ii}.lastPos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
+            hObs(ii, jj) = dot(obj.agents{ii}.pos - cPos, obj.agents{ii}.pos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
 
-            A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - cPos);
+            A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - cPos);
             % Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i
             r_i = obj.agents{ii}.collisionGeometry.radius;
             v_max_i = obj.agents{ii}.initialStepSize / obj.timestep;
@@ -84,52 +80,46 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
-    idx = idx + numel(hObs);
-
     % Set up domain constraints (walls and ceiling only)
     % Floor constraint is implicit with an obstacle corresponding to the
     % minimum allowed altitude, but I included it anyways
     h_xMin = 0.0; h_xMax = 0.0; h_yMin = 0.0; h_yMax = 0.0; h_zMin = 0.0; h_zMax = 0.0;
     for ii = 1:nAgents
         % X minimum
-        h_xMin = (obj.agents{ii}.lastPos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
+        h_xMin = (obj.agents{ii}.pos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
         b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % X maximum
-        h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.lastPos(1)) - obj.agents{ii}.collisionGeometry.radius;
+        h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.pos(1)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
         b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent;
         kk = kk + 1;
 
         % Y minimum
-        h_yMin = (obj.agents{ii}.lastPos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
+        h_yMin = (obj.agents{ii}.pos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
         b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % Y maximum
-        h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.lastPos(2)) - obj.agents{ii}.collisionGeometry.radius;
+        h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.pos(2)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
         b(kk) = obj.barrierGain * max(0, h_yMax)^obj.barrierExponent;
         kk = kk + 1;
 
         % Z minimum — enforce z >= minAlt + radius (not just z >= domain floor + radius)
-        h_zMin = (obj.agents{ii}.lastPos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
+        h_zMin = (obj.agents{ii}.pos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
         b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % Z maximum
-        h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.lastPos(3)) - obj.agents{ii}.collisionGeometry.radius;
+        h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.pos(3)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
         b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
         kk = kk + 1;
-
-        obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
-        idx = idx + 6;
     end
 
     if coder.target('MATLAB')
@@ -143,41 +133,21 @@ function [obj] = constrainMotion(obj)
     for ii = 1:(nAgents - 1)
         for jj = (ii + 1):nAgents
             if obj.constraintAdjacencyMatrix(ii, jj)
-                paddingFactor = 0.9; % Barrier at 90% of actual range; real comms still work beyond this
-                r_comms = paddingFactor * min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius]);
-                hComms(ii, jj) = r_comms^2 - norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2;
+                hComms(ii, jj) = min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])^2 - norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2;
 
-                A(kk, (3 * ii - 2):(3 * ii)) =  2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
+                A(kk, (3 * ii - 2):(3 * ii)) =  2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
                 A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
-
-                % One-step forward invariance: b = h/dt ensures h cannot
-                % go negative in a single timestep (linear approximation)
-                v_max_ij = max(obj.agents{ii}.initialStepSize, obj.agents{jj}.initialStepSize) / obj.timestep;
-                hMin = -4 * r_comms * v_max_ij * obj.timestep;
-                if norm(A(kk, :)) < 1e-9
-                    b(kk) = 0;
-                else
-                    b(kk) = max(hMin, hComms(ii, jj)) / obj.timestep;
-                end
+                b(kk) = obj.barrierGain * max(0, hComms(ii, jj))^obj.barrierExponent;
 
                 kk = kk + 1;
             end
         end
     end
-    obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
 
-    % Double-integrator: transform QP from velocity to acceleration space.
-    % Single-integrator constraint: A * v <= b
-    % Double-integrator: A * a <= (b - A * v_current) / dt
-    if obj.useDoubleIntegrator
-        v_flat = reshape(v', 3 * nAgents, 1);
-        b = (b - A * v_flat) / obj.timestep;
-    end
-
-    % Solve QP: minimize ||u - u_desired||²
-    uhat = reshape(u_desired', 3 * nAgents, 1);
+    % Solve QP program generated earlier
+    vhat = reshape(v', 3 * nAgents, 1);
     H = 2 * eye(3 * nAgents);
-    f = -2 * uhat;
+    f = -2 * vhat;
 
     % Update solution based on constraints
     if coder.target('MATLAB')
@@ -187,8 +157,8 @@ function [obj] = constrainMotion(obj)
     end
     opt = optimoptions("quadprog", "Display", "off", "Algorithm", "active-set", "UseCodegenSolver", true);
     x0 = zeros(size(H, 1), 1);
-    [uNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
-    uNew = reshape(uNew, 3, nAgents)';
+    [vNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
+    vNew = reshape(vNew, 3, nAgents)';
 
     if exitflag < 0
         % Infeasible or other hard failure: hold all agents at current positions
@@ -197,9 +167,9 @@ function [obj] = constrainMotion(obj)
         else
             fprintf("[constrainMotion] QP infeasible (exitflag=%d), holding positions\n", int16(exitflag));
         end
-        uNew = zeros(nAgents, 3);
+        vNew = zeros(nAgents, 3);
     elseif exitflag == 0
-        % Max iterations exceeded: use suboptimal solution already in uNew
+        % Max iterations exceeded: use suboptimal solution already in vNew
         if coder.target('MATLAB')
             warning("QP max iterations exceeded, using suboptimal solution.");
         else
@@ -207,16 +177,10 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    % Update agent state using the constrained control input
-    for ii = 1:size(uNew, 1)
-        if obj.useDoubleIntegrator
-            % uNew is constrained acceleration
-            obj.agents{ii}.vel = obj.agents{ii}.lastVel + uNew(ii, :) * obj.timestep;
-            obj.agents{ii}.pos = obj.agents{ii}.lastPos + obj.agents{ii}.vel * obj.timestep;
-        else
-            % uNew is constrained velocity
-            obj.agents{ii}.pos = obj.agents{ii}.lastPos + uNew(ii, :) * obj.timestep;
-        end
+    % Update the "next position" that was previously set by unconstrained
+    % GA using the constrained solution produced here
+    for ii = 1:size(vNew, 1)
+        obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
     end
 
     % Here we run this at the simulation level, but in reality there is no

@miSim/initialize.m

@@ -1,4 +1,4 @@
-function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology)
+function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "miSim")};
         domain (1, 1) {mustBeGeometry};
@@ -11,9 +11,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
         obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
         makePlots(1, 1) logical = true;
         makeVideo (1, 1) logical = true;
-        useDoubleIntegrator (1, 1) logical = false;
-        dampingCoeff (1, 1) double = 2.0;
-        useFixedTopology (1, 1) logical = false;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "miSim")};
@@ -89,18 +86,9 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
     obj.barrierExponent = barrierExponent;
     obj.minAlt = minAlt;
 
-    % Set dynamics model
-    obj.useDoubleIntegrator = useDoubleIntegrator;
-    obj.dampingCoeff = dampingCoeff;
-    obj.useFixedTopology = useFixedTopology;
-
-    % Compute adjacency matrix and network topology
+    % Compute adjacency matrix and lesser neighbors
     obj = obj.updateAdjacency();
-    if obj.useFixedTopology
-        obj.constraintAdjacencyMatrix = obj.adjacency;
-    else
     obj = obj.lesserNeighbor();
-    end
 
     % Set up times to iterate over
     obj.times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
@@ -116,34 +104,11 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
     % Create initial partitioning
     obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
 
-    % Determine number of barrier functions that will be necessary
-    if size(obj.agents, 1) < 2
-        nAAPairs = 0;
-    else
-        nAAPairs = nchoosek(size(obj.agents, 1), 2); % unique agent/agent pairs
-    end
-    nAOPairs = size(obj.agents, 1) * size(obj.obstacles, 1); % unique agent/obstacle pairs
-    nADPairs = size(obj.agents, 1) * 6; % agents x (4 walls + 1 floor + 1 ceiling)
-    nLNAPairs = sum(triu(obj.constraintAdjacencyMatrix, 1), "all");
-    obj.numBarriers = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
-
     if coder.target('MATLAB')
         % Initialize variable that will store agent positions for trail plots
         obj.posHist = NaN(size(obj.agents, 1), obj.maxIter + 1, 3);
         obj.posHist(1:size(obj.agents, 1), 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
 
-        % Initialize velocity history (zeros at t=0, all agents start at rest)
-        obj.velHist = zeros(size(obj.agents, 1), obj.maxIter + 1, 3);
-
-        % Initialize variable that will store barrier function values per timestep for analysis purposes
-        obj.barriers = NaN(obj.numBarriers, size(obj.times, 1));
-
-        % Initialize constraint adjacency history (nAgents x nAgents x nTimesteps)
-        nAgents = size(obj.agents, 1);
-        obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
-        obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
-
-
         % Set up plots showing initialized state
         obj = obj.plot();
 

@miSim/initializeFromCsv.m

@@ -79,23 +79,6 @@ assert(numel(BETA_TILT_VEC) == numAgents, ...
 
 numObstacles = scenario.numObstacles;
 
-% Dynamics model (optional columns — backward compatible with older CSVs)
-if isfield(scenario, 'useDoubleIntegrator')
-    USE_DOUBLE_INTEGRATOR = logical(scenario.useDoubleIntegrator);
-else
-    USE_DOUBLE_INTEGRATOR = false;
-end
-if isfield(scenario, 'dampingCoeff')
-    DAMPING_COEFF = scenario.dampingCoeff;
-else
-    DAMPING_COEFF = 2.0;
-end
-if isfield(scenario, 'useFixedTopology')
-    USE_FIXED_TOPOLOGY = logical(scenario.useFixedTopology);
-else
-    USE_FIXED_TOPOLOGY = false;
-end
-
 % ---- Build domain --------------------------------------------------------
 dom = rectangularPrism;
 dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
@@ -141,7 +124,6 @@ end
 
 % ---- Initialise simulation (plots and video disabled) --------------------
 obj = obj.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
-                     MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
-                     USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
+                     MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
 
 end

@miSim/miSim.m

@@ -7,6 +7,7 @@ classdef miSim
         timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
         maxIter = NaN; % maximum number of simulation iterations
         domain;
+        objective;
         obstacles; % geometries that define obstacles within the domain
         agents; % agents that move within the domain
         adjacency = false(0, 0); % Adjacency matrix representing communications network graph
@@ -17,17 +18,11 @@ classdef miSim
         barrierGain = NaN; % CBF gain parameter
         barrierExponent = NaN; % CBF exponent parameter
         minAlt = 0; % minimum allowable altitude (m)
-        useDoubleIntegrator = false; % false = single-integrator, true = double-integrator dynamics
-        dampingCoeff = 2.0; % velocity-proportional damping for double-integrator mode
-        useFixedTopology = false; % false = lesser neighbor (dynamic), true = fixed initial topology
         artifactName = "";
         f; % main plotting tiled layout figure
         fPerf; % performance plot figure
         % Indicies for various plot types in the main tiled layout figure
         spatialPlotIndices = [6, 4, 3, 2];
-        numBarriers = 0; % Number of barrier functions needed
-        barriers = []; % log barrier function values at each timestep for analysis
-        constraintAdjacencyHist = []; % log constraint adjacency matrix at each timestep
     end
 
     properties (Access = private)
@@ -45,7 +40,6 @@ classdef miSim
         performancePlot; % objects for sensor performance plot
 
         posHist; % data for trail plot
-        velHist; % velocity history (double-integrator mode)
         trailPlot; % objects for agent trail plot
 
         % Indicies for various plot types in the main tiled layout figure
@@ -67,6 +61,7 @@ classdef miSim
                 obj (1, 1) miSim
             end
             obj.domain = rectangularPrism;
+            obj.objective = sensingObjective;
             obj.obstacles = {rectangularPrism};
             obj.agents = {agent};
         end

@miSim/run.m

@@ -30,19 +30,12 @@ function [obj] = run(obj)
         obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
 
         % Determine desired communications links
-        if ~obj.useFixedTopology
         obj = obj.lesserNeighbor();
-        end
-
-        % Log constraint adjacency for this timestep
-        if coder.target('MATLAB')
-            obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
-        end
 
         % Moving
         % Iterate over agents to simulate their unconstrained motion
         for jj = 1:size(obj.agents, 1)
-            obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep);
+            obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents);
         end
 
         % Adjust motion determined by unconstrained gradient ascent using
@@ -50,9 +43,8 @@ function [obj] = run(obj)
         obj = constrainMotion(obj);
 
         if coder.target('MATLAB')
-            % Update agent position and velocity history arrays
+            % Update agent position history array
             obj.posHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
-            obj.velHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.vel, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
 
             % Update total performance
             obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(obj.timestepIndex+1), obj.agents))];
@@ -71,12 +63,10 @@ function [obj] = run(obj)
         end
     end
 
-    % Close video
     if coder.target('MATLAB')
         if obj.makeVideo
             % Close video file
             v.close();
         end
     end
-    
 end

@miSim/teardown.m

@@ -6,52 +6,25 @@ function obj = teardown(obj)
         obj (1, 1) {mustBeA(obj, "miSim")};
     end
 
-    % % Close plots
-    % close(obj.hf);
-    % close(obj.fPerf);
-    % close(obj.f);
-
-    % Log results into matfile
-    histPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", strcat(obj.artifactName, "_miSimHist.mat"));
-    out = struct("agent", repmat(struct("pos", [], "vel", [], "perf", [], "sensor", struct("alphaDist", [], "betaDist", [], "alphaTilt", [], "betaTilt", []), "collisionRadius", [], "commsRadius", []), size(obj.agents)), "perf", [], "barriers", [], "useDoubleIntegrator", [], "dampingCoeff", [], "useFixedTopology", []);
-
-    out.perf = obj.performance(1:(end - 1));
-    out.barriers = [zeros(size(obj.barriers(1:end, 1), 1), 1), obj.barriers(1:end, 1:(end - 1))];
-    out.dampingCoeff = obj.dampingCoeff;
-    out.useDoubleIntegrator = obj.useDoubleIntegrator;
-    out.useFixedTopology = obj.useFixedTopology;
-    out.constraintAdjacency = obj.constraintAdjacencyHist(:, :, 1:(end - 1));
-    for ii = 1:size(obj.agents, 1)
-        out.agent(ii).pos = squeeze(obj.posHist(ii, 1:(end - 1), 1:3));
-        out.agent(ii).vel = squeeze(obj.velHist(ii, 1:(end - 1), 1:3));
-        out.agent(ii).perf = obj.agents{ii}.performance(1:(end - 2));
-        out.agent(ii).sensor.alphaDist = obj.agents{ii}.sensorModel.alphaDist;
-        out.agent(ii).sensor.betaDist = obj.agents{ii}.sensorModel.betaDist;
-        out.agent(ii).sensor.alphaTilt = obj.agents{ii}.sensorModel.alphaTilt;
-        out.agent(ii).sensor.betaTilt = obj.agents{ii}.sensorModel.betaTilt;
-        out.agent(ii).collisionRadius = obj.agents{ii}.collisionGeometry.radius;
-        out.agent(ii).commsRadius = obj.agents{ii}.commsGeometry.radius;
-    end
-
-    save(histPath, "out");
+    % Close plots
+    close(obj.hf);
+    close(obj.fPerf);
+    close(obj.f);
 
     % reset parameters
     obj.timestep = NaN;
     obj.timestepIndex = NaN;
     obj.maxIter = NaN;
     obj.domain = rectangularPrism;
+    obj.objective = sensingObjective;
     obj.obstacles = cell(0, 1);
     obj.agents = cell(0, 1);
     obj.adjacency = NaN;
     obj.constraintAdjacencyMatrix = NaN;
-    obj.constraintAdjacencyHist = [];
     obj.partitioning = NaN;
     obj.performance = 0;
     obj.barrierGain = NaN;
     obj.barrierExponent = NaN;
-    obj.useDoubleIntegrator = false;
-    obj.dampingCoeff = 2.0;
-    obj.useFixedTopology = false;
     obj.artifactName = "";
 
 end

@miSim/validate.m

@@ -7,11 +7,11 @@ function validate(obj)
 
     %% Communications Network Validators
     if max(conncomp(graph(obj.adjacency))) ~= 1
-        error("Network is not connected");
+        warning("Network is not connected");
     end
 
     if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all")
-        error("Eliminated network connections that were necessary");
+        warning("Eliminated network connections that were necessary");
     end
 
     %% Obstacle Validators
@@ -21,8 +21,9 @@ function validate(obj)
             P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner);
             d = obj.agents{kk}.pos - P;
             if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2
-                error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
+                warning("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
             end
         end
     end
+
 end

@miSim/writeInits.m

@@ -14,21 +14,17 @@ function writeInits(obj)
     comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
     initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
     pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
-    obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, obj.obstacles, 'UniformOutput', false));
-    obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, obj.obstacles, 'UniformOutput', false));
+
 
     % Combine with simulation parameters
     inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ...
                     "discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
                     "sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
                     "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
-                    "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
-                    "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ...
-                    "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
+                    "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, "alphaDist", alphaDist, ...
+                    "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
                     ... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
-                    "pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
-                    "obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
-                    "objectiveIntegral", sum(obj.domain.objective.values(:)));
+                    "pos", pos);
 
     % Save all parameters to output file
     initsFile = strcat(obj.artifactName, "_miSimInits");

@sensingObjective/initialize.m

@@ -1,4 +1,4 @@
-function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum, objectiveMu, objectiveSigma)
+function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum)
     arguments (Input)
         obj (1,1) {mustBeA(obj, "sensingObjective")};
         objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")};
@@ -6,8 +6,6 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
         discretizationStep (1, 1) double = 1;
         protectedRange (1, 1) double = 1;
         sensorPerformanceMinimum (1, 1) double = 1e-6;
-        objectiveMu (:, 2) double = NaN(1, 2);
-        objectiveSigma (:, 2, 2) double = NaN(1, 2, 2);
     end
     arguments (Output)
         obj (1,1) {mustBeA(obj, "sensingObjective")};
@@ -39,13 +37,8 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
 
     % store ground position
     idx = obj.values == 1;
-    if any(isnan(objectiveMu))
     obj.groundPos = [obj.X(idx), obj.Y(idx)];
     obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
-    else
-        obj.groundPos = objectiveMu;
-    end
-    obj.objectiveSigma = objectiveSigma;
 
-    assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective");
+    assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
 end

@sensingObjective/initializeRandomMvnpdf.m

@@ -11,7 +11,7 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
 
     % Set random objective position
     mu = domain.minCorner;
-    while domain.distance(mu) < protectedRange * 1.01
+    while domain.distance(mu) < protectedRange
         mu = domain.random();
     end
 

@sensingObjective/sensingObjective.m

@@ -2,8 +2,7 @@ classdef sensingObjective
     % Sensing objective definition parent class
     properties (SetAccess = private, GetAccess = public)
         label = "";
-        groundPos = NaN(1, 2);
-        objectiveSigma = NaN(1, 2, 2);
+        groundPos = [NaN, NaN];
         discretizationStep = NaN;
         X = [];
         Y = [];

aerpaw/config/client1.yaml

@@ -12,8 +12,8 @@ tdm:
 
 # ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
 origin:
-  lat: 35.72595214250436
-  lon: -78.69917609299937
+  lat: 35.72550610629396
+  lon: -78.70019657805574
   alt: 0.0  # Alt=0 means ENU z directly becomes target altitude above home
 # Environment-specific settings
 environments:
@@ -32,7 +32,7 @@ environments:
     mavlink:
       ip: "192.168.32.26"
       port: 14550
-    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
+    # Controller runs on host machine (192.168.122.1 from E-VM perspective)
     controller:
-      ip: "192.168.109.1"
+      ip: "192.168.122.1"
       port: 5000

aerpaw/config/client2.yaml

@@ -12,8 +12,8 @@ tdm:
 
 # ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
 origin:
-  lat: 35.72595214250436
-  lon: -78.69917609299937
+  lat: 35.72550610629396
+  lon: -78.70019657805574
   alt: 0.0  # Alt=0 means ENU z directly becomes target altitude above home
 # Environment-specific settings
 environments:
@@ -32,7 +32,7 @@ environments:
     mavlink:
       ip: "192.168.32.26"
       port: 14550
-    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
+    # Controller runs on host machine (192.168.122.1 from E-VM perspective)
     controller:
-      ip: "192.168.109.1"
+      ip: "192.168.122.1"
       port: 5000

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

aerpaw/controller.coderprj

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

aerpaw/impl/controller_main.cpp

@@ -3,15 +3,10 @@
 #include "controller_impl.h" // TCP implementation header
 
 int main() {
-    // Derive numClients from initialPositions in scenario.csv
-    double targets[MAX_CLIENTS_PER_PARAM * 3];
-    int numClients = loadInitialPositions("config/scenario.csv",
-                                          targets, MAX_CLIENTS_PER_PARAM);
-    if (numClients < 1) {
-        std::cerr << "Failed to parse numClients from scenario.csv\n";
-        return 1;
-    }
-    std::cout << "Parsed " << numClients << " UAV(s) from scenario.csv\n";
+    // Number of clients to handle
+    int numClients = 2;  // for now
+
+    std::cout << "Initializing TCP server...\n";
 
     // Call MATLAB-generated server function
     controller(numClients);

aerpaw/radio/CSwSNRRX.py

@@ -267,10 +267,6 @@ class CSwSNRRX(gr.top_block):
             '/root/Quality', num_uavs, slot_duration, guard_interval)
         self.blocks_file_sink_0 = TdmTaggedFileSink(
             '/root/Power', num_uavs, slot_duration, guard_interval)
-        self.blocks_file_sink_noisefloor = TdmTaggedFileSink(
-            '/root/NoiseFloor', num_uavs, slot_duration, guard_interval)
-        self._freqoffset_file = open('/root/FreqOffset', 'w')
-        self._freqoffset_file.write('tx_uav_id,value\n')
         self.blocks_divide_xx_0 = blocks.divide_ff(1)
         self.blocks_complex_to_real_0_0 = blocks.complex_to_real(1)
         self.blocks_complex_to_real_0 = blocks.complex_to_real(1)
@@ -314,7 +310,6 @@ class CSwSNRRX(gr.top_block):
         self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_add_const_vxx_0, 0))
         self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_sub_xx_0, 0))
         self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_sub_xx_0, 1))
-        self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_file_sink_noisefloor, 0))
         self.connect((self.blocks_stream_to_vector_0_0, 0), (self.epy_block_0, 0))
         self.connect((self.blocks_sub_xx_0, 0), (self.blocks_file_sink_0_0_0, 0))
         self.connect((self.blocks_vector_to_stream_0_0, 0), (self.blocks_keep_m_in_n_0, 0))
@@ -326,26 +321,6 @@ class CSwSNRRX(gr.top_block):
         self.connect((self.freq_xlating_fft_filter_ccc_0_0, 0), (self.blocks_stream_to_vector_0_0, 0))
         self.connect((self.uhd_usrp_source_0, 0), (self.blocks_multiply_xx_0, 0))
 
-        ##################################################
-        # Frequency offset polling thread
-        ##################################################
-        def _freq_offset_probe():
-            frame_dur = slot_duration * num_uavs
-            while True:
-                val = self.digital_fll_band_edge_cc_0_0.get_frequency()
-                freq_hz = val * samp_rate / (2 * math.pi)
-                now = time.time()
-                slot_time = now % frame_dur
-                current_slot = int(slot_time / slot_duration)
-                time_into_slot = slot_time - current_slot * slot_duration
-                tx_id = -1 if time_into_slot < guard_interval else current_slot
-                self._freqoffset_file.write(f'{tx_id},{freq_hz}\n')
-                self._freqoffset_file.flush()
-                time.sleep(0.01)
-        _freq_offset_thread = threading.Thread(target=_freq_offset_probe)
-        _freq_offset_thread.daemon = True
-        _freq_offset_thread.start()
-
 
     def get_args(self):
         return self.args

aerpaw/radio/startchannelsounderRXGRC.sh

@@ -20,4 +20,4 @@ else
 fi
 
 cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
-python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
+python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS

aerpaw/radio/startchannelsounderTXGRC.sh

@@ -20,4 +20,4 @@ else
 fi
 
 cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
-python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
+python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS

aerpaw/radio/updateScripts.sh

@@ -1,15 +1,7 @@
 #!/bin/bash
 
-# Drop in replacements for channel sounder scripts
 cp startchannelsounderRXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
 cp startchannelsounderTXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
+
 cp CSwSNRRX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
 cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
-
-# Replace start scripts
-cp ../scripts/startexperiment.sh /root/.
-cp ../scripts/startRadio.sh /root/Profiles/ProfileScripts/Radio/.
-cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
-
-echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
-echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"

aerpaw/results/plotRadioLogs.m

@@ -24,25 +24,16 @@ function [f, R] = plotRadioLogs(resultsPath)
         R{ii}(bad, :) = [];
     end
 
-    % Compute path loss from Power (post-processing)
-    % Power = 20*log10(peak_mag) - rxGain; path loss = txGain - rxGain - Power
-    txGain_dB = 76;   % from startchannelsounderTXGRC.sh GAIN_TX
-    rxGain_dB = 30;   % from startchannelsounderRXGRC.sh GAIN_RX
-    for ii = 1:numel(R)
-        R{ii}.PathLoss = txGain_dB - rxGain_dB - R{ii}.Power;
-        R{ii}.FreqOffset = R{ii}.FreqOffset / 1e6; % Hz to MHz
-    end
-
     % Build legend labels and color map for up to 4 UAVs
     nUAV = numel(R);
     colors = lines(nUAV * nUAV);
     styles = ["-o", "-s", "-^", "-d", "-v", "-p", "-h", "-<", "->", "-+", "-x", "-*"];
 
-    metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
-    yLabels     = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
+    metricNames = ["SNR", "Power", "Quality"];
+    yLabels     = ["SNR (dB)", "Power (dB)", "Quality"];
 
     f = figure;
-    tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
+    tl = tiledlayout(3, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
 
     for mi = 1:numel(metricNames)
         ax = nexttile(tl);

aerpaw/results/readRadioLogs.m

@@ -4,19 +4,19 @@ function R = readRadioLogs(logPath)
     end
 
     arguments (Output)
-        R (:, 8) table;
+        R (:, 6) table;
     end
 
     % Extract receiving UAV ID from directory name (e.g. "uav0_..." → 0)
     [~, dirName] = fileparts(logPath);
     rxID = int32(sscanf(dirName, 'uav%d'));
 
-    metrics = ["quality", "snr", "power", "noisefloor", "freqoffset"];
+    metrics = ["quality", "snr", "power"];
     logs = dir(logPath);
     logs = logs(endsWith({logs(:).name}, metrics + "_log.txt"));
 
-    R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), ...
-        'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
+    R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), ...
+        'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
 
     for ii = 1:numel(logs)
         filepath = fullfile(logs(ii).folder, logs(ii).name);
@@ -43,15 +43,13 @@ function R = readRadioLogs(logPath)
         val = data{3};
 
         n = numel(ts);
-        t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), ...
-            'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
+        t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), ...
+            'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
 
         switch metric
             case "snr",     t.SNR = val;
             case "power",   t.Power = val;
             case "quality", t.Quality = val;
-            case "noisefloor", t.NoiseFloor = val;
-            case "freqoffset", t.FreqOffset = val;
         end
 
         R = [R; t]; %#ok<AGROW>

aerpaw/results/resultsAnalysis.m

@@ -1,5 +1,5 @@
 %% Plot AERPAW logs (trajectory, radio)
-resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % Define path to results copied from AERPAW platform
+resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "t1"); % Define path to results copied from AERPAW platform
 
 % Plot GPS logged data and scenario information (domain, objective, obstacles)
 seaToGroundLevel = 110; % measured approximately from USGS national map viewer

aerpaw/run_uav.sh

@@ -32,8 +32,8 @@ else
     exit 1
 fi
 
-# Client config file: 2nd argument > AERPAW_CLIENT_CONFIG env var > default
-CONFIG_FILE="${2:-${AERPAW_CLIENT_CONFIG:-config/client.yaml}}"
+# Client config file (optional 2nd argument)
+CONFIG_FILE="${2:-config/client.yaml}"
 if [ ! -f "$CONFIG_FILE" ]; then
     echo "Error: Config file not found: $CONFIG_FILE"
     exit 1
@@ -59,7 +59,7 @@ echo "[run_uav] MAVLink connection: $CONN"
 
 # Run via aerpawlib
 echo "[run_uav] Starting UAV runner..."
-python3 -u -m aerpawlib \
+python3 -m aerpawlib \
     --script client.uav_runner \
     --conn "$CONN" \
     --vehicle drone

aerpaw/scripts/startRadio.sh

@@ -1,100 +0,0 @@
-#!/bin/bash
-
-# Derive number of UAVs from scenario.csv
-NUM_UAVS=$(python3 -c "
-import csv, os
-csv_path = '/root/miSim/aerpaw/config/scenario.csv'
-with open(csv_path, 'r') as f:
-    reader = csv.reader(f, skipinitialspace=True)
-    header = [h.strip() for h in next(reader)]
-    row = next(reader)
-col = header.index('initialPositions')
-vals = [v.strip() for v in row[col].strip().split(',') if v.strip()]
-print(len(vals) // 3)
-" 2>/dev/null || echo 0)
-
-cd $PROFILE_DIR"/ProfileScripts/Radio/Helpers"
-
-if [ "$NUM_UAVS" -eq 2 ]; then
-    # Direct 1-to-1 mode: UAV 0 = TX only, UAV 1 = RX only
-    echo "[Radio] 2-UAV direct mode: UAV_ID=$UAV_ID"
-
-    if [ "$UAV_ID" -eq 0 ]; then
-        # TX only (--num-uavs 1 disables TDM muting)
-        screen -S txGRC -dm \
-               bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh --num-uavs 1 \
-               2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
-    else
-        # RX only (--num-uavs 1 disables TDM tagging)
-        screen -S rxGRC -dm \
-               bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh --num-uavs 1 \
-               2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
-
-        screen -S power -dm \
-               bash -c "stdbuf -oL -eL tail -F /root/Power\
-                2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
-
-        screen -S quality -dm \
-               bash -c "stdbuf -oL -eL tail -F /root/Quality\
-                2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
-
-        screen -S snr -dm \
-               bash -c "stdbuf -oL -eL tail -F /root/SNR\
-                2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
-
-        screen -S noisefloor -dm \
-              bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
-                2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
-
-        screen -S freqoffset -dm \
-               bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
-                2>&1 | ts $TS_FORMAT \
-               | tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
-    fi
-else
-    # 3+ UAVs: full TDM mode — every node runs both TX and RX
-    echo "[Radio] TDM mode: $NUM_UAVS UAVs, UAV_ID=$UAV_ID"
-
-    screen -S rxGRC -dm \
-           bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh \
-           2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
-
-    screen -S power -dm \
-           bash -c "stdbuf -oL -eL tail -F /root/Power\
-            2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
-
-    screen -S quality -dm \
-           bash -c "stdbuf -oL -eL tail -F /root/Quality\
-            2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
-
-    screen -S snr -dm \
-           bash -c "stdbuf -oL -eL tail -F /root/SNR\
-            2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
-
-    screen -S noisefloor -dm \
-          bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
-            2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
-
-    screen -S freqoffset -dm \
-           bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
-            2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
-
-    screen -S txGRC -dm \
-           bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh \
-           2>&1 | ts $TS_FORMAT \
-           | tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
-fi
-
-cd -

aerpaw/scripts/startVehicle.sh

@@ -1,30 +0,0 @@
-#!/bin/bash
-
-### Sample GPS logger portion
-# use vehicle type generic to skip the arming requirement
-export VEHICLE_TYPE="${VEHICLE_TYPE:-generic}"
-
-# GPS Logger sample application (this does not move the vehicle)
-
-#cd $PROFILE_DIR"/ProfileScripts/Vehicle/Helpers"
-#
-#screen -S vehicle -dm \
-#       bash -c "stdbuf -oL -eL ./gpsLoggerHelper.sh \
-#       2> >(ts $TS_FORMAT >> $RESULTS_DIR/${LOG_PREFIX}_vehicle_log_err.txt) \
-#       | ts $TS_FORMAT \
-#       | tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"
-#
-#cd -
-
-### Actual control portion (custom)
-export VEHICLE_TYPE="${VEHICLE_TYPE:-drone}" # out of rover, drone, generic
-
-cd /root/miSim/aerpaw
-
-# Use screen/ts/tee aerpawism from sample script
-screen -S vehicle -dm \
-       bash -c "stdbuf -oL -eL ./run_uav.sh testbed \
-       | ts $TS_FORMAT \
-       | tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"     
-
-cd -

aerpaw/scripts/startVehicle_controller.sh

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

aerpaw/scripts/startexperiment.sh

@@ -1,50 +0,0 @@
-#!/bin/bash
-/root/stopexperiment.sh
-
-source /root/.ap-set-experiment-env.sh
-source /root/.bashrc
-
-# set path to client config YAML
-export AERPAW_CLIENT_CONFIG=/root/miSim/aerpaw/config/client1.yaml
-
-export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
-export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
-export PYTHONPATH=/usr/local/lib/python3/dist-packages/
-export EXP_NUMBER=${EXP_NUMBER:-1}
-
-if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
-    export VEHICLE_TYPE=drone
-elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
-    export VEHICLE_TYPE=rover
-else
-    export VEHICLE_TYPE=none
-fi
-
-if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
-    export LAUNCH_MODE=EMULATION
-elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
-    export LAUNCH_MODE=TESTBED
-else
-    export LAUNCH_MODE=none
-fi
-
-# prepare results directory
-export UAV_ID=$(python3 -c "import yaml; print(yaml.safe_load(open('$AERPAW_CLIENT_CONFIG'))['uav_id'])")
-export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
-export RESULTS_DIR="/root/Results/uav${UAV_ID}_${RESULTS_DIR_TIMESTAMP}"
-mkdir -p "$RESULTS_DIR"
-
-export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
-export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
-
-export TX_FREQ=3.32e9
-export RX_FREQ=3.32e9
-
-export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
-cd $PROFILE_DIR"/ProfileScripts"
-
-./Radio/startRadio.sh
-#./Traffic/startTraffic.sh
-./Vehicle/startVehicle.sh
-
-schedule_stop.sh 30

aerpaw/scripts/startexperiment_controller.sh

@@ -1,47 +0,0 @@
-#!/bin/bash
-/root/stopexperiment.sh
-
-source /root/.ap-set-experiment-env.sh
-source /root/.bashrc
-
-export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
-export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
-export PYTHONPATH=/usr/local/lib/python3/dist-packages/
-export EXP_NUMBER=${EXP_NUMBER:-1}
-
-if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
-    export VEHICLE_TYPE=drone
-elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
-    export VEHICLE_TYPE=rover
-else
-    export VEHICLE_TYPE=none
-fi
-
-if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
-    export LAUNCH_MODE=EMULATION
-elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
-    export LAUNCH_MODE=TESTBED
-else
-    export LAUNCH_MODE=none
-fi
-
-# prepare results directory
-export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
-export RESULTS_DIR="/root/Results/controller_${RESULTS_DIR_TIMESTAMP}"
-mkdir -p "$RESULTS_DIR"
-
-export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
-export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
-
-export TX_FREQ=3.32e9
-export RX_FREQ=3.32e9
-
-export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
-cd $PROFILE_DIR"/ProfileScripts"
-
-screen -S controller -dm \
-	bash -c "stdbuf -oL -eL ./Vehicle/startVehicle.sh \
-	| ts $TS_FORMAT \
-	| tee $RESULTS_DIR/$LOG_PREFIX\_controller_log.txt"
-
-schedule_stop.sh 30

resources/project/EEtUlUb-dLAdf0KpMVivaUlztwA/YoWkWDdbwwiRDjC6Inll7Thh1K8d.xml

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

resources/project/EEtUlUb-dLAdf0KpMVivaUlztwA/YoWkWDdbwwiRDjC6Inll7Thh1K8p.xml

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

resources/project/Gnz6T47dAsmf4YcBHB3EkpeZeYA/p7b0T5lVDU-D8JiROZNSX56qOhcp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/7zvVfoOGOecwrnesPxOvEZRcJNYd.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/7zvVfoOGOecwrnesPxOvEZRcJNYp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/LU7BdyAbq1VWsP1tcW099qs0_cYd.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/LU7BdyAbq1VWsP1tcW099qs0_cYp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/M4B1x4nVEuLmUODrHewQHG0CDHsp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/Wf9PEeTALvEX83cew4fZfavy2ewd.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/Wf9PEeTALvEX83cew4fZfavy2ewp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/bRP3MIwZ4PcWx9PloJbVyWC00JAd.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/bRP3MIwZ4PcWx9PloJbVyWC00JAp.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/oczvKa9PTzIQRYD1e6ccXbiMz_wd.xml

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

resources/project/p7b0T5lVDU-D8JiROZNSX56qOhc/oczvKa9PTzIQRYD1e6ccXbiMz_wp.xml

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

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/hUjTM8Yelb7ggxXFg7nBPm4NKQop.xml

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

test/parametricTestSuite.m

@@ -57,16 +57,13 @@ classdef parametricTestSuite < matlab.unittest.TestCase
             end
 
             % Set up simulation
-            tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, tc.makePlots, tc.makeVideo, logical(params.useDoubleIntegrator), params.dampingCoeff, logical(params.useFixedTopology));
+            tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, tc.makePlots, tc.makeVideo);
 
             % Save simulation parameters to output file
             tc.testClass.writeInits();
 
             % Run
             tc.testClass = tc.testClass.run();
-
-            % Save results and clean up
-            tc.testClass = tc.testClass.teardown();
         end
         function csv_parametric_tests_random_agents(tc)
             % Read in parameters to iterate over

test/test_miSim.m

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

util/objectiveFunctionWrapper.m

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