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
@@ -60,22 +60,16 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    idx = length(h(triu(true(size(h)), 1)));    
-    if coder.target('MATLAB')
-	obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
-    end
-    idx = idx + 1;
-
     hObs = NaN(nAgents, size(obj.obstacles, 1));
     % 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;
@@ -86,56 +80,51 @@ function [obj] = constrainMotion(obj)
         end
     end
 
-    if coder.target('MATLAB')
-	obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
-    end
-    idx = idx + numel(hObs);
-
     % Set up domain constraints (walls and ceiling only)
     % 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;
+    end
 
     if coder.target('MATLAB')
-	    obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
-        end
-	idx = idx + 6;
+        % 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
@@ -144,44 +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
 
-    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
-    % 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')
@@ -191,8 +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
@@ -201,9 +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
@@ -211,16 +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)';
@@ -109,39 +97,18 @@ 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
     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/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

@@ -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
@@ -54,6 +48,7 @@ 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
@@ -66,13 +61,12 @@ classdef miSim
                 obj (1, 1) miSim
             end
             obj.domain = rectangularPrism;
+            obj.objective = sensingObjective;
             obj.obstacles = {rectangularPrism};
             obj.agents = {agent};
         end
         [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), :)');
-    domLabels = ["X Min", "X Max", "Y Min", "Y Max", "Z Min", "Z Max"];
-    legendStrings = strings(nDom, 1);
-    for ii = 1:size(obj.agents, 1)
-        legendStrings((ii - 1) * 6 + (1:6)) = sprintf("A%d ", ii) + domLabels;
-    end
-    legend(obj.hf.Children(1).Children(1), legendStrings, "Location", "bestoutside");
+    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)');
+    legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], "Location", "bestoutside");
     hold(obj.hf.Children(1).Children(2), "off");
 
     nexttile(obj.hf.Children(1));

@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/updatePlots.m

@@ -61,15 +61,13 @@ function [obj] = updatePlots(obj)
     end
 
     % Update h function plots
-    nCA  = size(obj.caPlot, 1);
-    nObs = size(obj.obsPlot, 1);
-    for ii = 1:nCA
-        obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
+    for ii = 1:size(obj.caPlot, 1)
+        obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
     end
-    for ii = 1:nObs
-        obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, obj.timestepIndex);
+    for ii = 1:size(obj.obsPlot, 1)
+        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/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
@@ -20,9 +20,10 @@ function validate(obj)
         for kk = 1:size(obj.agents, 1)
             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 - 1e-3
-                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
+            if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2
+                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

@@ -5,37 +5,26 @@ function writeInits(obj)
     arguments (Output)
     end
 
-    % User-supplied obstacles only: initialize() appends a floor obstacle at
-    % the end when minAlt > 0, so exclude it here to avoid double-counting on
-    % reconstruction (initializeFromInits re-adds the floor via minAlt).
-    numInputObs = size(obj.obstacles, 1) - (obj.minAlt > 0);
-    userObstacles = obj.obstacles(1:numInputObs);
-
     % Collect agent parameters
     collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
     alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
     betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
     alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
-    betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
+    betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
     comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
     initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
     pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
-    obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, userObstacles, 'UniformOutput', false));
-    obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, userObstacles, '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, ...
-                    "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
-                    "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
-                    "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
+                    "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
+                    "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, ...
-                    "domainMin", obj.domain.minCorner, "domainMax", obj.domain.maxCorner, ...
-                    "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

@@ -11,16 +11,16 @@ 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
 
     % 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/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/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

@@ -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:
@@ -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 (192.168.122.1 from E-VM perspective)
     controller:
-      ip: "192.168.112.1"
+      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:
@@ -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 (192.168.122.1 from E-VM perspective)
     controller:
-      ip: "192.168.112.1"
+      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, 100, 30.0, 0.1, 2.0, 5, 1, 1, "6.0, 6.0", "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

@@ -133,31 +133,6 @@
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                   <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 id="28" type="coderapp.internal.codertype.PrimitiveType">
-                  <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"/>
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               </Types>
             </coderapp.internal.interface.project.Interface>
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@@ -1161,7 +1094,7 @@
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           </MF0>

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 * 2;
+MAX_TARGETS = MAX_CLIENTS;
 
 % Allocate targets array (MAX_TARGETS x 3)
 targets = zeros(MAX_TARGETS, 3);
@@ -34,28 +33,6 @@ 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.
-if ~coder.target('MATLAB')
-    TRANSIT_ALT_BASE = 25.0;  % must match drone.takeoff() altitude in uav_runner.py
-    TRANSIT_ALT_STEP = 12.1;  % vertical separation per UAV (m); must exceed 2*collisionRadius
-    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 = 45;
 MAX_OBSTACLES_CTRL  = int32(8);

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

@@ -1,16 +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"
-echo "REMEMBER! Manually copy startVehicle_controller.sh to ~/Profiles/ProfileScripts/Vehicle/startVehicle.sh on the fixed node"

aerpaw/results/plotGpsLogs.m

@@ -1,8 +1,7 @@
-function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
+function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
     arguments (Input)
         logDirs (1, 1) string;
         seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
-        plotWholeFlight (1, 1) logical = false;
     end
     arguments (Output)
         f (1, 1) matlab.ui.Figure;
@@ -49,10 +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;
-            stopIdx = length(verticalSpeed);
-        end
+        % startIdx = 1;
+        % stopIdx = length(verticalSpeed);
 
         % Convert LLA trajectory data to ENU for external analysis
         % NaN out entries outside the algorithm flight range so they don't plot

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);
@@ -31,39 +31,25 @@ function R = readRadioLogs(logPath)
         end
 
         fid = fopen(filepath, 'r');
-        % Skip header lines: some files have 2 tail-error lines + 1 column
-        % header ("tx_uav_id,value"), others start with data immediately.
-        % Read until a line that looks like a data record, then rewind to it.
-        dataPattern = '^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+\] [-\d]';
-        linePos = ftell(fid);
-        while true
-            line = fgetl(fid);
-            if ~ischar(line)
-                break;  % EOF
-            end
-            if ~isempty(regexp(line, dataPattern, 'once'))
-                fseek(fid, linePos, 'bof');  % rewind to start of this line
-                break;
-            end
-            linePos = ftell(fid);
+        % Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value)
+        for k = 1:3
+            fgetl(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};
 
         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

@@ -1,10 +1,9 @@
 %% Plot AERPAW logs (trajectory, radio)
-resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % Define path to results copied from AERPAW platform
+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
-plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
-% [fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
+[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
 
 % Plot radio statistics
 [fRadio, R] = plotRadioLogs(resultsPath);
@@ -22,7 +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)

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/71xh8lboMaPoa5Dmw3ABwzIozfw/bjgcAyD7dxJIgrUo3yHl5f1-iksp.xml

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

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/Hp7WImb16Wc_c7gK28oUydAFVts/EhSD3dO3mU2KP9IqbTVz7g60j5Ap.xml

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

resources/project/QVXvsR5cXQzGBi9QgRUFaflegRY/SltMFP7zr3UZsLPdRi9OyWAN7pMp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/_1CKOWXf9sLpzeC642i06VHUH0Qd.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<Info>
-    <Category UUID="FileClassCategory">
-        <Label UUID="design"/>
-    </Category>
-</Info>

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/_1CKOWXf9sLpzeC642i06VHUH0Qp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/abbdKJ8UvIXKWL0sR9NW0pEJSNId.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<Info>
-    <Category UUID="FileClassCategory">
-        <Label UUID="design"/>
-    </Category>
-</Info>

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/abbdKJ8UvIXKWL0sR9NW0pEJSNIp.xml

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

resources/project/Vq0hyJJCG53DJ8wxA_8WUihyBpg/H9TIrKqi-fFOWfgKFbIj3tQLZ3Yp.xml

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

resources/project/ls4G1ReemmlA4lw5Sxijq_iTPE0/YTBPi7yO4zYK5U1mxnqJDcdXNYkp.xml

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

resources/project/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_cYp.xml

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

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/bRP3MIwZ4PcWx9PloJbVyWC00JAp.xml

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

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/pjpApCZ_IyThRbNNVtyf0HS9lGA/OvzpqD8IaJL2rl4SaQSOPQ-QRMkp.xml

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

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

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

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

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/71xh8lboMaPoa5Dmw3ABwzIozfwd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/71xh8lboMaPoa5Dmw3ABwzIozfwp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Hp7WImb16Wc_c7gK28oUydAFVtsd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Hp7WImb16Wc_c7gK28oUydAFVtsp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/QVXvsR5cXQzGBi9QgRUFaflegRYd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/QVXvsR5cXQzGBi9QgRUFaflegRYp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Vq0hyJJCG53DJ8wxA_8WUihyBpgd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/Vq0hyJJCG53DJ8wxA_8WUihyBpgp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/ls4G1ReemmlA4lw5Sxijq_iTPE0d.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/ls4G1ReemmlA4lw5Sxijq_iTPE0p.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/pjpApCZ_IyThRbNNVtyf0HS9lGAd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/pjpApCZ_IyThRbNNVtyf0HS9lGAp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/soCFsvL91lhqvUw-h8HkHCtfsiwd.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/soCFsvL91lhqvUw-h8HkHCtfsiwp.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/yqgj8VLvTZ-pn09SsztajkpKW1Ed.xml

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

resources/project/q138eJA8Ym4eSfM3RFMVvg63QtU/yqgj8VLvTZ-pn09SsztajkpKW1Ep.xml

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

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/hUjTM8Yelb7ggxXFg7nBPm4NKQod.xml

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

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/hUjTM8Yelb7ggxXFg7nBPm4NKQop.xml

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

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

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

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

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

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

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

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

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

test/parametricTestSuite.m

@@ -34,8 +34,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
 
             % Define scenario according to CSV specification
             tc.domain = tc.domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
-            objectiveSigma = reshape(params.objectiveVar, [1 2 2]);
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, objectiveSigma), tc.domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum, params.objectivePos, objectiveSigma);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), tc.domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
 
             agents = cell(size(params.initialPositions, 2) / 3, 1);
             for ii = 1:size(agents, 1)
@@ -58,16 +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
@@ -82,8 +78,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
             for ii = 1:size(params.timestep, 1)
                 % Set up square domain
                 tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
-                objectiveCenter = [.75 * l, 0.75 * l];
-                tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper(objectiveCenter), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii), objectiveCenter);
+                tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii));
                 
                 % Initialize agents
                 agents = cell(params.numAgents(ii), 1);

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;
@@ -166,8 +163,8 @@ classdef test_miSim < matlab.unittest.TestCase
                     end
 
                     % Initialize candidate agent collision geometry
-                    candidateGeometry = spherical;
-                    candidateGeometry = candidateGeometry.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
+                    candidateGeometry = rectangularPrism;
+                    candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION);
 
                     % Initialize candidate agent sensor model
                     tc.sensor = tc.sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
@@ -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]);
@@ -437,12 +434,12 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [7, 6]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent};
-            geometry1 = spherical;
-            geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
+            geometry1 = rectangularPrism;
+            geometry1 = geometry1.initialize([[tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
             
             % Initialize agent sensor model with fixed parameters
             tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3);
@@ -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
@@ -466,7 +463,7 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [3, 7]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent};
@@ -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();
@@ -504,7 +501,7 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5.2195]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent;};
@@ -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();
@@ -588,7 +585,7 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent;};
@@ -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)));
@@ -633,7 +630,7 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent; agent; agent; agent;};
@@ -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( ...
@@ -683,7 +680,7 @@ classdef test_miSim < matlab.unittest.TestCase
             tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
 
             % make basic sensing objective
-            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
+            tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
         
             % Initialize agent collision geometry
             tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
@@ -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( ...
@@ -728,128 +725,6 @@ classdef test_miSim < matlab.unittest.TestCase
                   0, 0, 0, 1, 1, 1, 1;
                   0, 0, 0, 0, 0, 1, 1; ]));
         end
-        function miSim_initializeFromInits(tc)
-            % Build a minimal valid simulation, write it to a matfile, reload
-            % via initializeFromInits, assert round-trip consistency, then
-            % delete the file.  No plotting or video at any stage.
-
-            % Obstacles
-            nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
-            tc.obstacles = cell(nGeom, 1);
-            for ii = 1:nGeom
-                badCandidate = true;
-                while badCandidate
-                    tc.obstacles{ii} = rectangularPrism;
-                    tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, ...
-                        sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, ...
-                        tc.domain, tc.minAlt);
-                    if ~tc.obstacleCollisionCheck(tc.obstacles(1:(ii - 1)), tc.obstacles{ii})
-                        badCandidate = false;
-                    end
-                end
-            end
-
-            % Agents
-            nAgents = tc.minAgents;
-            tc.agents = cell(nAgents, 1);
-            tc.collisionRanges = tc.minCollisionRange + rand(nAgents, 1) * (tc.maxCollisionRange - tc.minCollisionRange);
-            tc.commsRanges = tc.minCommsRange + rand(nAgents, 1) * (tc.maxCommsRange - tc.minCommsRange);
-
-            for ii = 1:nAgents
-                initInvalid = true;
-                while initInvalid
-                    if ii == 1
-                        candidatePos = tc.domain.random();
-                        candidatePos(3) = tc.minAlt + rand * 3;
-                        while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
-                            candidatePos = tc.domain.random();
-                            candidatePos(3) = tc.minAlt + rand * 3;
-                        end
-                    else
-                        candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.commsRanges(ii) / sqrt(2));
-                        candidatePos(3) = tc.minAlt + rand * 3;
-                    end
-
-                    if ~tc.domain.contains(candidatePos), continue; end
-                    if agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2), continue; end
-
-                    % Connectivity check
-                    connections = false(1, ii - 1);
-                    for jj = 1:(ii - 1)
-                        if norm(tc.agents{jj}.pos - candidatePos) <= min(tc.commsRanges([ii, jj]))
-                            connections(jj) = true;
-                            for kk = 1:size(tc.obstacles, 1)
-                                if tc.obstacles{kk}.containsLine(tc.agents{jj}.pos, candidatePos)
-                                    connections(jj) = false;
-                                end
-                            end
-                        end
-                    end
-                    if ii ~= 1 && ~any(connections), continue; end
-
-                    geom = spherical;
-                    geom = geom.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
-                    tc.sensor = sigmoidSensor;
-                    tc.sensor = tc.sensor.initialize( ...
-                        tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), ...
-                        tc.betaDistMin  + rand * (tc.betaDistMax  - tc.betaDistMin), ...
-                        tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), ...
-                        tc.betaTiltMin  + rand * (tc.betaTiltMax  - tc.betaTiltMin));
-                    newAgent = agent;
-                    newAgent = newAgent.initialize(candidatePos, geom, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize);
-
-                    % Domain / obstacle / agent collision checks
-                    violation = false;
-                    for jj = 1:size(newAgent.collisionGeometry.vertices, 1)
-                        if ~tc.domain.contains(newAgent.collisionGeometry.vertices(jj, 1:3))
-                            violation = true; break;
-                        end
-                    end
-                    if violation, continue; end
-                    for kk = 1:size(tc.obstacles, 1)
-                        if geometryIntersects(tc.obstacles{kk}, newAgent.collisionGeometry)
-                            violation = true; break;
-                        end
-                    end
-                    if violation, continue; end
-                    for kk = 1:(ii - 1)
-                        if geometryIntersects(tc.agents{kk}.collisionGeometry, newAgent.collisionGeometry)
-                            violation = true; break;
-                        end
-                    end
-                    if newAgent.pos(3) - newAgent.collisionGeometry.radius <= tc.minAlt
-                        violation = true;
-                    end
-                    if violation, continue; end
-
-                    initInvalid = false;
-                    tc.agents{ii} = newAgent;
-                end
-            end
-
-            % Initialize first sim (no plots / video)
-            sim1 = miSim;
-            sim1 = sim1.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, ...
-                tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, false, false, ...
-                tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
-
-            % Write inits and build file path
-            sim1.writeInits();
-            initsFile = fullfile(matlab.project.rootProject().RootFolder, "sandbox", ...
-                strcat(sim1.artifactName, "_miSimInits.mat"));
-
-            % Load via initializeFromInits
-            sim2 = miSim;
-            sim2 = sim2.initializeFromInits(initsFile);
-
-            % Assertions
-            tc.assertEqual(size(sim2.agents, 1), size(sim1.agents, 1));
-            tc.assertEqual(sim2.maxIter, sim1.maxIter);
-            tc.assertEqual(sim2.barrierGain, sim1.barrierGain);
-
-            % Cleanup
-            delete(initsFile);
-        end
     end
 
     methods

util/objectiveFunctionWrapper.m

@@ -4,12 +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