organizing

.gitignore

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

.gitmodules

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

@agent/agent.m

@@ -6,6 +6,8 @@ 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

@@ -15,6 +15,9 @@ 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)
+function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useDoubleIntegrator, dampingCoeff, dt)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         domain (1, 1) {mustBeGeometry};
@@ -6,11 +6,21 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
         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(:))
@@ -75,20 +85,25 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
     targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
     gradNorm = norm(gradC);
 
-    % Compute unconstrained next position.
+    % Compute unconstrained next state
-    % Guard against near-zero gradient: when sensor performance is saturated
+    if useDoubleIntegrator
-    % or near-zero across the whole partition, rateFactor -> Inf and pNext
+        % Double-integrator: gradient produces desired acceleration with damping
-    % explodes. Stay put instead.
+        if gradNorm < 1e-100
-    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
-        pNext = obj.pos + (targetRate / gradNorm) * gradC;
+        % Single-integrator: gradient directly sets position step
+        if gradNorm >= 1e-100
+            obj.pos = obj.pos + (targetRate / gradNorm) * gradC;
+        end
     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

@@ -8,118 +8,128 @@ function [obj] = constrainMotion(obj)
 
     nAgents = size(obj.agents, 1);
 
-    if nAgents < 2
+    % Compute current velocity and desired control input
-        nAAPairs = 0;
+    v = zeros(nAgents, 3);        % current velocity (for drift term in DI mode)
-    else
+    u_desired = zeros(nAgents, 3); % desired control: velocity (SI) or acceleration (DI)
-        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;
+        if obj.useDoubleIntegrator
+            v(ii, :) = obj.agents{ii}.lastVel;
+            u_desired(ii, :) = (obj.agents{ii}.vel - obj.agents{ii}.lastVel) / obj.timestep;
+        else
+            v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
+            u_desired(ii, :) = v(ii, :);
+        end
     end
-    if all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all")
+    if ~obj.useDoubleIntegrator && (all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all"))
-        % Agents are not attempting to move, so there is no motion to be
+        % Single-integrator: agents are not attempting to move
-        % constrained
+        return;
+    end
+    if obj.useDoubleIntegrator && all(u_desired == 0, "all") && all(v == 0, "all")
+        % Double-integrator: no desired acceleration and no existing velocity
         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(total, 3 * nAgents);
+    A = zeros(obj.numBarriers, 3 * nAgents);
-    b = zeros(total, 1);
+    b = zeros(obj.numBarriers, 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}.pos - obj.agents{jj}.pos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
+            h(ii, jj) = norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
             h(jj, ii) = h(ii, jj);
 
-            A(kk, (3 * ii - 2):(3 * ii)) =  -2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
+            A(kk, (3 * ii - 2):(3 * ii)) =  -2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
             A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
             % Slack derived from existing params: recovery velocity = max gradient approach velocity.
             % Correction splits between 2 agents, so |A| = 2*r_sum
             r_sum_ij = obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius;
             v_max_ij = max(obj.agents{ii}.initialStepSize, obj.agents{jj}.initialStepSize) / obj.timestep;
-            slack = -(4 * r_sum_ij * v_max_ij / obj.barrierGain)^(1 / obj.barrierExponent);
+            hMin = -(4 * r_sum_ij * v_max_ij / obj.barrierGain)^(1 / obj.barrierExponent);
             if norm(A(kk, :)) < 1e-9
                 % Agents are coincident: A-row is zero, so b < 0 would make
                 % 0 ≤ b unsatisfiable. Fall back to b = 0 (no correction possible).
                 b(kk) = 0;
             else
-                b(kk) = obj.barrierGain * max(slack, h(ii, jj))^obj.barrierExponent;
+                b(kk) = obj.barrierGain * max(hMin, h(ii, jj))^obj.barrierExponent;
             end
             kk = kk + 1;
         end
     end
 
+    idx = length(h(triu(true(size(h)), 1)));
+    obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
+    idx = idx + 1;
+
     hObs = NaN(nAgents, size(obj.obstacles, 1));
     % Set up obstacle avoidance constraints
     for ii = 1:nAgents
         for jj = 1:size(obj.obstacles, 1)
             % find closest position to agent on/in obstacle
-            cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.pos);
+            cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.lastPos);
 
-            hObs(ii, jj) = dot(obj.agents{ii}.pos - cPos, obj.agents{ii}.pos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
+            hObs(ii, jj) = dot(obj.agents{ii}.lastPos - cPos, obj.agents{ii}.lastPos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
 
-            A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - cPos);
+            A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - cPos);
             % Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i
             r_i = obj.agents{ii}.collisionGeometry.radius;
             v_max_i = obj.agents{ii}.initialStepSize / obj.timestep;
-            h_floor_i = -(2 * r_i * v_max_i / obj.barrierGain)^(1 / obj.barrierExponent);
+            hMin = -(2 * r_i * v_max_i / obj.barrierGain)^(1 / obj.barrierExponent);
-            b(kk) = obj.barrierGain * max(h_floor_i, hObs(ii, jj))^obj.barrierExponent;
+            b(kk) = obj.barrierGain * max(hMin, hObs(ii, jj))^obj.barrierExponent;
 
             kk = kk + 1;
         end
     end
 
+    obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
+    idx = idx + numel(hObs);
+
     % Set up domain constraints (walls and ceiling only)
     % Floor constraint is implicit with an obstacle corresponding to the
     % minimum allowed altitude, but I included it anyways
     h_xMin = 0.0; h_xMax = 0.0; h_yMin = 0.0; h_yMax = 0.0; h_zMin = 0.0; h_zMax = 0.0;
     for ii = 1:nAgents
         % X minimum
-        h_xMin = (obj.agents{ii}.pos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
+        h_xMin = (obj.agents{ii}.lastPos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
         b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % X maximum
-        h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.pos(1)) - obj.agents{ii}.collisionGeometry.radius;
+        h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.lastPos(1)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
         b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent;
         kk = kk + 1;
 
         % Y minimum
-        h_yMin = (obj.agents{ii}.pos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
+        h_yMin = (obj.agents{ii}.lastPos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
         b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % Y maximum
-        h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.pos(2)) - obj.agents{ii}.collisionGeometry.radius;
+        h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.lastPos(2)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
         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}.pos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
+        h_zMin = (obj.agents{ii}.lastPos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
         b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent;
         kk = kk + 1;
 
         % Z maximum
-        h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.pos(3)) - obj.agents{ii}.collisionGeometry.radius;
+        h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.lastPos(3)) - obj.agents{ii}.collisionGeometry.radius;
         A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
         b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
         kk = kk + 1;
+
+        obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
+        idx = idx + 6;
     end
 
     if coder.target('MATLAB')
@@ -133,21 +143,41 @@ function [obj] = constrainMotion(obj)
     for ii = 1:(nAgents - 1)
         for jj = (ii + 1):nAgents
             if obj.constraintAdjacencyMatrix(ii, jj)
-                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;
+                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;
 
-                A(kk, (3 * ii - 2):(3 * ii)) =  2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
+                A(kk, (3 * ii - 2):(3 * ii)) =  2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
                 A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
-                b(kk) = obj.barrierGain * max(0, hComms(ii, jj))^obj.barrierExponent;
+
+                % 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
 
                 kk = kk + 1;
             end
         end
     end
+    obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
 
-    % Solve QP program generated earlier
+    % Double-integrator: transform QP from velocity to acceleration space.
-    vhat = reshape(v', 3 * nAgents, 1);
+    % 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);
     H = 2 * eye(3 * nAgents);
-    f = -2 * vhat;
+    f = -2 * uhat;
 
     % Update solution based on constraints
     if coder.target('MATLAB')
@@ -157,23 +187,36 @@ function [obj] = constrainMotion(obj)
     end
     opt = optimoptions("quadprog", "Display", "off", "Algorithm", "active-set", "UseCodegenSolver", true);
     x0 = zeros(size(H, 1), 1);
-    [vNew, ~, exitflag, m] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
+    [uNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
-    if coder.target('MATLAB')
+    uNew = reshape(uNew, 3, nAgents)';
-        assert(exitflag == 1, sprintf("quadprog failure... %s%s", newline, m.message));
-    end
-    vNew = reshape(vNew, 3, nAgents)';
 
-    if exitflag <= 0
+    if exitflag < 0
+        % Infeasible or other hard failure: hold all agents at current positions
         if coder.target('MATLAB')
-            warning("QP failed, continuing with unconstrained solution...")
+            warning("QP infeasible (exitflag=%d), holding positions.", int16(exitflag));
+        else
+            fprintf("[constrainMotion] QP infeasible (exitflag=%d), holding positions\n", int16(exitflag));
+        end
+        uNew = zeros(nAgents, 3);
+    elseif exitflag == 0
+        % Max iterations exceeded: use suboptimal solution already in uNew
+        if coder.target('MATLAB')
+            warning("QP max iterations exceeded, using suboptimal solution.");
+        else
+            fprintf("[constrainMotion] QP max iterations exceeded, using suboptimal solution\n");
         end
-        vNew = v;
     end
 
-    % Update the "next position" that was previously set by unconstrained
+    % Update agent state using the constrained control input
-    % GA using the constrained solution produced here
+    for ii = 1:size(uNew, 1)
-    for ii = 1:size(vNew, 1)
+        if obj.useDoubleIntegrator
-        obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
+            % 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
     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)
+function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "miSim")};
         domain (1, 1) {mustBeGeometry};
@@ -11,6 +11,9 @@ 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")};
@@ -86,9 +89,18 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
     obj.barrierExponent = barrierExponent;
     obj.minAlt = minAlt;
 
-    % Compute adjacency matrix and lesser neighbors
+    % Set dynamics model
+    obj.useDoubleIntegrator = useDoubleIntegrator;
+    obj.dampingCoeff = dampingCoeff;
+    obj.useFixedTopology = useFixedTopology;
+
+    % Compute adjacency matrix and network topology
     obj = obj.updateAdjacency();
-    obj = obj.lesserNeighbor();
+    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)';
@@ -104,11 +116,33 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
     % Create initial partitioning
     obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
 
+    % Determine number of barrier functions that will be necessary
+    if size(obj.agents, 1) < 2
+        nAAPairs = 0;
+    else
+        nAAPairs = nchoosek(size(obj.agents, 1), 2); % unique agent/agent pairs
+    end
+    nAOPairs = size(obj.agents, 1) * size(obj.obstacles, 1); % unique agent/obstacle pairs
+    nADPairs = size(obj.agents, 1) * 6; % agents x (4 walls + 1 floor + 1 ceiling)
+    nLNAPairs = sum(triu(obj.constraintAdjacencyMatrix, 1), "all");
+    obj.numBarriers = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
+
     if coder.target('MATLAB')
         % Initialize variable that will store agent positions for trail plots
         obj.posHist = NaN(size(obj.agents, 1), obj.maxIter + 1, 3);
         obj.posHist(1:size(obj.agents, 1), 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
 
+        % Initialize velocity history (zeros at t=0, all agents start at rest)
+        obj.velHist = zeros(size(obj.agents, 1), obj.maxIter + 1, 3);
+
+        % Initialize variable that will store barrier function values per timestep for analysis purposes
+        obj.barriers = NaN(obj.numBarriers, size(obj.times, 1));
+
+        % Initialize constraint adjacency history (nAgents x nAgents x nTimesteps)
+        nAgents = size(obj.agents, 1);
+        obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
+        obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
+
         % Set up plots showing initialized state
         obj = obj.plot();
 

@miSim/initializeFromCsv.m

@@ -79,6 +79,23 @@ 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");
@@ -124,6 +141,7 @@ end
 
 % ---- Initialise simulation (plots and video disabled) --------------------
 obj = obj.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
-                     MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
+                     MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
+                     USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
 
 end

@miSim/miSim.m

@@ -7,7 +7,6 @@ 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
@@ -18,8 +17,17 @@ 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)
@@ -31,17 +39,16 @@ classdef miSim
         % Plot objects
         makePlots = true; % enable/disable simulation plotting (performance implications)
         makeVideo = true; % enable/disable VideoWriter (performance implications)
-        f; % main plotting tiled layout figure
         connectionsPlot; % objects for lines connecting agents in spatial plots
         graphPlot; % objects for abstract network graph plot
         partitionPlot; % objects for partition plot
         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
-        spatialPlotIndices = [6, 4, 3, 2];
         objectivePlotIndices = [6, 4];
         networkGraphIndex = 5;
         partitionGraphIndex = 1;
@@ -60,7 +67,6 @@ classdef miSim
                 obj (1, 1) miSim
             end
             obj.domain = rectangularPrism;
-            obj.objective = sensingObjective;
             obj.obstacles = {rectangularPrism};
             obj.agents = {agent};
         end

@miSim/run.m

@@ -30,12 +30,19 @@ function [obj] = run(obj)
         obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
 
         % Determine desired communications links
-        obj = obj.lesserNeighbor();
+        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.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep);
         end
 
         % Adjust motion determined by unconstrained gradient ascent using
@@ -43,8 +50,9 @@ function [obj] = run(obj)
         obj = constrainMotion(obj);
 
         if coder.target('MATLAB')
-            % Update agent position history array
+            % Update agent position and velocity history arrays
             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))];
@@ -63,10 +71,12 @@ 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

@@ -6,25 +6,52 @@ function obj = teardown(obj)
         obj (1, 1) {mustBeA(obj, "miSim")};
     end
 
-    % Close plots
+    % % Close plots
-    close(obj.hf);
+    % close(obj.hf);
-    close(obj.fPerf);
+    % close(obj.fPerf);
-    close(obj.f);
+    % 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");
 
     % reset parameters
     obj.timestep = NaN;
     obj.timestepIndex = NaN;
     obj.maxIter = NaN;
     obj.domain = rectangularPrism;
-    obj.objective = sensingObjective;
     obj.obstacles = cell(0, 1);
     obj.agents = cell(0, 1);
     obj.adjacency = NaN;
     obj.constraintAdjacencyMatrix = NaN;
+    obj.constraintAdjacencyHist = [];
     obj.partitioning = NaN;
     obj.performance = 0;
     obj.barrierGain = NaN;
     obj.barrierExponent = NaN;
+    obj.useDoubleIntegrator = false;
+    obj.dampingCoeff = 2.0;
+    obj.useFixedTopology = false;
     obj.artifactName = "";
 
 end

@miSim/validate.m

@@ -7,11 +7,11 @@ function validate(obj)
 
     %% Communications Network Validators
     if max(conncomp(graph(obj.adjacency))) ~= 1
-        warning("Network is not connected");
+        error("Network is not connected");
     end
 
     if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all")
-        warning("Eliminated network connections that were necessary");
+        error("Eliminated network connections that were necessary");
     end
 
     %% Obstacle Validators
@@ -20,10 +20,9 @@ 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
+            if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 - 1e-3
-                warning("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
+                error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, - dot(d, d) + obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
             end
         end
     end
-
 end

@miSim/writeInits.m

@@ -14,6 +14,8 @@ function writeInits(obj)
     comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
     initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
     pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
+    obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, obj.obstacles, 'UniformOutput', false));
+    obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, obj.obstacles, 'UniformOutput', false));
 
 
     % Combine with simulation parameters
@@ -21,10 +23,13 @@ function writeInits(obj)
                     "discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
                     "sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
                     "barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
-                    "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, "alphaDist", alphaDist, ...
+                    "numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
-                    "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
+                    "useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ...
+                    "alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
                     ... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
-                    "pos", pos);
+                    "pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
+                    "obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
+                    "objectiveIntegral", sum(obj.domain.objective.values(:)));
 
     % 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)
+function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum, objectiveMu, objectiveSigma)
     arguments (Input)
         obj (1,1) {mustBeA(obj, "sensingObjective")};
         objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")};
@@ -6,6 +6,8 @@ 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")};
@@ -37,8 +39,13 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
 
     % store ground position
     idx = obj.values == 1;
-    obj.groundPos = [obj.X(idx), obj.Y(idx)];
+    if any(isnan(objectiveMu))
-    obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
+        obj.groundPos = [obj.X(idx), obj.Y(idx)];
+        obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
+    else
+        obj.groundPos = objectiveMu;
+    end
+    obj.objectiveSigma = objectiveSigma;
 
-    assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
+    assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
 end

@sensingObjective/initializeRandomMvnpdf.m

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

@sensingObjective/sensingObjective.m

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

aerpaw/client/uav_runner.py

@@ -46,8 +46,9 @@ class MessageType(IntEnum):
     POSITION         = 8
 
 
-AERPAW_DIR = Path(__file__).parent.parent
+AERPAW_DIR = Path('/root/miSim/aerpaw')
-CONFIG_FILE = AERPAW_DIR / "config" / "client.yaml"
+CONFIG_FILE = Path(os.environ.get('AERPAW_CLIENT_CONFIG',
+                                  AERPAW_DIR / "config" / "client.yaml"))
 
 
 def load_config():
@@ -115,8 +116,9 @@ def _gps_log_row(vehicle, line_num, writer):
 
 async def _gps_log_loop(drone):
     """Background async task that logs GPS data at 1Hz."""
-    host = platform.node()
+    results_dir = os.environ.get('RESULTS_DIR', '/root/Results')
-    filename = f"/root/Results/GPS_DATA_{host}_{datetime.datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}.csv"
+    log_prefix = os.environ.get('LOG_PREFIX', datetime.datetime.now().strftime('%Y-%m-%d_%H_%M_%S'))
+    filename = os.path.join(results_dir, f"{log_prefix}_gps_log.csv")
     print(f"[UAV] GPS logging to {filename}")
     line_num = 1
     try:

aerpaw/config/client1.yaml

@@ -1,9 +1,19 @@
 # AERPAW UAV (Client) Configuration
 
+# Unique 0-indexed UAV identifier (each UAV must have a distinct value)
+uav_id: 0
+
+# TDM (Time-Division Multiplexing) radio settings
+# All UAVs share a common frequency; each transmits only during its time slot.
+# Slot assignment uses wall-clock modular arithmetic (GPS/NTP synced).
+tdm:
+  slot_duration: 0.5      # seconds per slot
+  guard_interval: 0.05    # seconds of silence at slot boundaries
+
 # ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
 origin:
-  lat: 35.72550610629396
+  lat: 35.72595214250436
-  lon: -78.70019657805574
+  lon: -78.69917609299937
   alt: 0.0  # Alt=0 means ENU z directly becomes target altitude above home
 # Environment-specific settings
 environments:
@@ -22,7 +32,7 @@ environments:
     mavlink:
       ip: "192.168.32.26"
       port: 14550
-    # Controller runs on host machine (192.168.122.1 from E-VM perspective)
+    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
     controller:
-      ip: "192.168.122.1"
+      ip: "192.168.109.1"
       port: 5000

aerpaw/config/client2.yaml

@@ -0,0 +1,38 @@
+# AERPAW UAV (Client) Configuration
+
+# Unique 0-indexed UAV identifier (each UAV must have a distinct value)
+uav_id: 1
+
+# TDM (Time-Division Multiplexing) radio settings
+# All UAVs share a common frequency; each transmits only during its time slot.
+# Slot assignment uses wall-clock modular arithmetic (GPS/NTP synced).
+tdm:
+  slot_duration: 0.5      # seconds per slot
+  guard_interval: 0.05    # seconds of silence at slot boundaries
+
+# ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
+origin:
+  lat: 35.72595214250436
+  lon: -78.69917609299937
+  alt: 0.0  # Alt=0 means ENU z directly becomes target altitude above home
+# Environment-specific settings
+environments:
+  local:
+    # MAVLink connection for SITL simulation (UDP)
+    mavlink:
+      ip: "127.0.0.1"
+      port: 14550
+    # Controller server address
+    controller:
+      ip: "127.0.0.1"
+      port: 5000
+
+  testbed:
+    # AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
+    mavlink:
+      ip: "192.168.32.26"
+      port: 14550
+    # Controller runs on host machine (192.168.109.1 from E-VM perspective)
+    controller:
+      ip: "192.168.109.1"
+      port: 5000

aerpaw/config/scenario.csv

@@ -1,2 +1,2 @@
-timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax
+timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
-5, 100, 30.0, 0.1, 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"
+1, 150, 30.0, 0.1, 2.0, 1, 1, 1, "5.0, 5.0", "25.0, 25.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "80.0, 80.0, 80.0", "55.0, 55.0", "40, 25, 25, 40", 0.15, "15.0, 10.0, 40.0, 5.0, 10.0, 45.0", 1, "1.0, 25.0, 0.0", "30.0, 30.0, 50.0", 1, 2.0, 1

aerpaw/controller.coderprj

@@ -128,6 +128,16 @@
                   <Size type="coderapp.internal.codertype.Dimension"/>
                   <Size type="coderapp.internal.codertype.Dimension"/>
                 </Types>
+                <Types id="26" type="coderapp.internal.codertype.PrimitiveType">
+                  <ClassName>int32</ClassName>
+                  <Size type="coderapp.internal.codertype.Dimension"/>
+                  <Size type="coderapp.internal.codertype.Dimension"/>
+                </Types>
+                <Types id="27" type="coderapp.internal.codertype.PrimitiveType">
+                  <ClassName>int32</ClassName>
+                  <Size type="coderapp.internal.codertype.Dimension"/>
+                  <Size type="coderapp.internal.codertype.Dimension"/>
+                </Types>
               </Types>
             </coderapp.internal.interface.project.Interface>
           </MF0>
@@ -519,575 +529,569 @@
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                   <File type="coderapp.internal.util.mfz.FileSpec">
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+                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/feasibleX0ForWorkingSet.cpp</Path>
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                   <Type>GENERATED_SOURCE</Type>
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                 <Artifacts id="66" type="coderapp.internal.build.mfz.CodegenArtifact">
                   <File type="coderapp.internal.util.mfz.FileSpec">
-                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/factoryConstruct.h</Path>
+                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/feasibleX0ForWorkingSet.h</Path>
                   </File>
                   <Type>GENERATED_SOURCE</Type>
                 </Artifacts>
                 <Artifacts id="67" type="coderapp.internal.build.mfz.CodegenArtifact">
                   <File type="coderapp.internal.util.mfz.FileSpec">
-                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/feasibleX0ForWorkingSet.cpp</Path>
+                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/feasibleratiotest.cpp</Path>
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+                    <Path>/home/kdee/Desktop/miSim/aerpaw/codegen/feasibleratiotest.h</Path>
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aerpaw/guidance_step.m

@@ -135,7 +135,7 @@ if isInit
 
         % --- Build obstacle list from flat arrays ---
         coder.varsize('obstacleList', [8, 1], [1, 0]);
-        obstacleList = cell(int32(0), 1);
+        obstacleList = repmat({rectangularPrism}, numObstacles, 1);
         for ii = 1:numObstacles
             obs = rectangularPrism;
             obs = obs.initialize([obstacleMin(ii, :); obstacleMax(ii, :)], ...

aerpaw/impl/controller_main.cpp

@@ -1,12 +1,17 @@
 #include <iostream>
-#include "controller.h" 
+#include "controller.h"
 #include "controller_impl.h" // TCP implementation header
 
 int main() {
-    // Number of clients to handle
+    // Derive numClients from initialPositions in scenario.csv
-    int numClients = 2;  // for now
+    double targets[MAX_CLIENTS_PER_PARAM * 3];
-
+    int numClients = loadInitialPositions("config/scenario.csv",
-    std::cout << "Initializing TCP server...\n";
+                                          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";
 
     // Call MATLAB-generated server function
     controller(numClients);

aerpaw/radio/CSwSNRTX.py

@@ -0,0 +1,336 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+#
+# SPDX-License-Identifier: GPL-3.0
+#
+# GNU Radio Python Flow Graph
+# Title: CSwSNRTX
+# Author: Ozgur Ozdemir
+# Description: Channel Sounder Transmitter with offset freq
+# GNU Radio version: v3.8.5.0-6-g57bd109d
+
+from gnuradio import analog
+from gnuradio import blocks
+from gnuradio import digital
+from gnuradio import filter
+from gnuradio.filter import firdes
+from gnuradio import gr
+import sys
+import signal
+import threading
+from argparse import ArgumentParser
+from gnuradio.eng_arg import eng_float, intx
+from gnuradio import eng_notation
+from gnuradio import uhd
+import time
+
+
+def derive_num_uavs_from_csv(csv_path=None):
+    """Derive number of UAVs from scenario.csv by counting initial positions.
+
+    The initialPositions column contains a quoted comma-separated list of
+    x,y,z triples.  num_uavs = len(values) / 3.
+    """
+    import os, csv
+    if csv_path is None:
+        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')
+    init_pos = row[col].strip()
+    n_vals = len([v.strip() for v in init_pos.split(',') if v.strip()])
+    if n_vals % 3 != 0:
+        raise ValueError(f"initialPositions has {n_vals} values; expected a multiple of 3")
+    return n_vals // 3
+
+
+class TdmScheduler(threading.Thread):
+    """Daemon thread that mutes/unmutes a GNU Radio mute_cc block on a
+    wall-clock TDM schedule.
+
+    Slot assignment:  current_slot = floor(utc_time / slot_duration) % num_uavs
+    Guard interval:   the first *guard_interval* seconds of every slot are
+                      always muted to avoid TX overlap due to clock skew.
+    """
+
+    def __init__(self, mute_block, uav_id, num_uavs,
+                 slot_duration=0.5, guard_interval=0.05):
+        super().__init__(daemon=True)
+        self.mute_block = mute_block
+        self.uav_id = uav_id
+        self.num_uavs = num_uavs
+        self.slot_duration = slot_duration
+        self.guard_interval = guard_interval
+        self._stop_event = threading.Event()
+
+    def run(self):
+        print(f"[TDM] Scheduler started: uav_id={self.uav_id}, "
+              f"num_uavs={self.num_uavs}, slot={self.slot_duration}s, "
+              f"guard={self.guard_interval}s")
+        while not self._stop_event.is_set():
+            now = time.time()
+            slot_time = now % (self.slot_duration * self.num_uavs)
+            current_slot = int(slot_time / self.slot_duration)
+            time_into_slot = slot_time - current_slot * self.slot_duration
+
+            my_slot = (current_slot == self.uav_id)
+            in_guard = (time_into_slot < self.guard_interval)
+
+            should_mute = (not my_slot) or in_guard
+            self.mute_block.set_mute(should_mute)
+
+            # Sleep ~1 ms for responsive timing without busy-waiting
+            self._stop_event.wait(0.001)
+
+    def stop(self):
+        self._stop_event.set()
+
+
+class CSwSNRTX(gr.top_block):
+
+    def __init__(self, args='', freq=3.32e9, gaintx=76, offset=250e3, samp_rate=2e6, sps=16,
+                 uav_id=0, num_uavs=1, slot_duration=0.5, guard_interval=0.05):
+        gr.top_block.__init__(self, "CSwSNRTX")
+
+        ##################################################
+        # Parameters
+        ##################################################
+        self.args = args
+        self.freq = freq
+        self.gaintx = gaintx
+        self.offset = offset
+        self.samp_rate = samp_rate
+        self.sps = sps
+        self.uav_id = uav_id
+        self.num_uavs = num_uavs
+        self.slot_duration = slot_duration
+        self.guard_interval = guard_interval
+
+        ##################################################
+        # Variables
+        ##################################################
+        self.alpha = alpha = 0.99
+
+        ##################################################
+        # Blocks
+        ##################################################
+        self.uhd_usrp_sink_0 = uhd.usrp_sink(
+            ",".join(("", args)),
+            uhd.stream_args(
+                cpu_format="fc32",
+                args='',
+                channels=list(range(0,1)),
+            ),
+            '',
+        )
+        self.uhd_usrp_sink_0.set_center_freq(freq, 0)
+        self.uhd_usrp_sink_0.set_gain(gaintx, 0)
+        self.uhd_usrp_sink_0.set_antenna('TX/RX', 0)
+        self.uhd_usrp_sink_0.set_samp_rate(samp_rate)
+        self.uhd_usrp_sink_0.set_time_unknown_pps(uhd.time_spec())
+        self.root_raised_cosine_filter_0 = filter.fir_filter_ccf(
+            1,
+            firdes.root_raised_cosine(
+                sps,
+                samp_rate,
+                samp_rate/sps,
+                alpha,
+                10*sps+1))
+        self.interp_fir_filter_xxx_0 = filter.interp_fir_filter_ccc(sps, [1]+[0]*(sps-1))
+        self.interp_fir_filter_xxx_0.declare_sample_delay(0)
+        self.digital_glfsr_source_x_0 = digital.glfsr_source_b(12, True, 0, 1)
+        self.digital_chunks_to_symbols_xx_0 = digital.chunks_to_symbols_bc((-1,1), 1)
+        self.blocks_multiply_xx_0 = blocks.multiply_vcc(1)
+        self.blocks_multiply_const_vxx_0 = blocks.multiply_const_cc(1/1.58)
+        self.blocks_mute_0 = blocks.mute_cc(True)  # TDM: start muted
+        self.analog_sig_source_x_0 = analog.sig_source_c(samp_rate, analog.GR_COS_WAVE, offset, 1, 0, 0)
+
+
+        ##################################################
+        # Connections
+        ##################################################
+        self.connect((self.analog_sig_source_x_0, 0), (self.blocks_multiply_xx_0, 1))
+        self.connect((self.blocks_multiply_const_vxx_0, 0), (self.blocks_mute_0, 0))
+        self.connect((self.blocks_mute_0, 0), (self.uhd_usrp_sink_0, 0))
+        self.connect((self.blocks_multiply_xx_0, 0), (self.blocks_multiply_const_vxx_0, 0))
+        self.connect((self.digital_chunks_to_symbols_xx_0, 0), (self.interp_fir_filter_xxx_0, 0))
+        self.connect((self.digital_glfsr_source_x_0, 0), (self.digital_chunks_to_symbols_xx_0, 0))
+        self.connect((self.interp_fir_filter_xxx_0, 0), (self.root_raised_cosine_filter_0, 0))
+        self.connect((self.root_raised_cosine_filter_0, 0), (self.blocks_multiply_xx_0, 0))
+
+
+    def get_args(self):
+        return self.args
+
+    def set_args(self, args):
+        self.args = args
+
+    def get_freq(self):
+        return self.freq
+
+    def set_freq(self, freq):
+        self.freq = freq
+        self.uhd_usrp_sink_0.set_center_freq(self.freq, 0)
+
+    def get_gaintx(self):
+        return self.gaintx
+
+    def set_gaintx(self, gaintx):
+        self.gaintx = gaintx
+        self.uhd_usrp_sink_0.set_gain(self.gaintx, 0)
+
+    def get_offset(self):
+        return self.offset
+
+    def set_offset(self, offset):
+        self.offset = offset
+        self.analog_sig_source_x_0.set_frequency(self.offset)
+
+    def get_samp_rate(self):
+        return self.samp_rate
+
+    def set_samp_rate(self, samp_rate):
+        self.samp_rate = samp_rate
+        self.analog_sig_source_x_0.set_sampling_freq(self.samp_rate)
+        self.root_raised_cosine_filter_0.set_taps(firdes.root_raised_cosine(self.sps, self.samp_rate, self.samp_rate/self.sps, self.alpha, 10*self.sps+1))
+        self.uhd_usrp_sink_0.set_samp_rate(self.samp_rate)
+
+    def get_sps(self):
+        return self.sps
+
+    def set_sps(self, sps):
+        self.sps = sps
+        self.interp_fir_filter_xxx_0.set_taps([1]+[0]*(self.sps-1))
+        self.root_raised_cosine_filter_0.set_taps(firdes.root_raised_cosine(self.sps, self.samp_rate, self.samp_rate/self.sps, self.alpha, 10*self.sps+1))
+
+    def get_alpha(self):
+        return self.alpha
+
+    def set_alpha(self, alpha):
+        self.alpha = alpha
+        self.root_raised_cosine_filter_0.set_taps(firdes.root_raised_cosine(self.sps, self.samp_rate, self.samp_rate/self.sps, self.alpha, 10*self.sps+1))
+
+
+def argument_parser():
+    description = 'Channel Sounder Transmitter with offset freq'
+    parser = ArgumentParser(description=description)
+    parser.add_argument(
+        "--args", dest="args", type=str, default='',
+        help="Set args [default=%(default)r]")
+    parser.add_argument(
+        "--freq", dest="freq", type=eng_float, default="3.32G",
+        help="Set freq [default=%(default)r]")
+    parser.add_argument(
+        "--gaintx", dest="gaintx", type=eng_float, default="76.0",
+        help="Set gaintx [default=%(default)r]")
+    parser.add_argument(
+        "--offset", dest="offset", type=eng_float, default="250.0k",
+        help="Set offset [default=%(default)r]")
+    parser.add_argument(
+        "--samp-rate", dest="samp_rate", type=eng_float, default="2.0M",
+        help="Set samp_rate [default=%(default)r]")
+    parser.add_argument(
+        "--sps", dest="sps", type=intx, default=16,
+        help="Set sps [default=%(default)r]")
+    parser.add_argument(
+        "--uav-id", dest="uav_id", type=int, default=None,
+        help="TDM slot index for this UAV (0-indexed). "
+             "If omitted, read from config/client.yaml.")
+    parser.add_argument(
+        "--num-uavs", dest="num_uavs", type=int, default=None,
+        help="Total number of UAVs (TDM slots). "
+             "If omitted, derived from config/scenario.csv.")
+    parser.add_argument(
+        "--slot-duration", dest="slot_duration", type=float, default=None,
+        help="TDM slot duration in seconds [default: 0.5 or from client.yaml]")
+    parser.add_argument(
+        "--guard-interval", dest="guard_interval", type=float, default=None,
+        help="TDM guard interval in seconds [default: 0.05 or from client.yaml]")
+    return parser
+
+
+def _resolve_tdm_options(options):
+    """Fill in TDM parameters from client.yaml / scenario.csv when not
+    provided on the command line."""
+    import os, yaml
+    cfg_dir = '/root/miSim/aerpaw/config'
+    env_cfg = os.environ.get('AERPAW_CLIENT_CONFIG', '')
+    if env_cfg:
+        yaml_path = env_cfg if os.path.isabs(env_cfg) else os.path.join('/root/miSim/aerpaw', env_cfg)
+    else:
+        yaml_path = os.path.join(cfg_dir, 'client.yaml')
+
+    cfg = {}
+    if os.path.isfile(yaml_path):
+        with open(yaml_path, 'r') as f:
+            cfg = yaml.safe_load(f) or {}
+
+    tdm_cfg = cfg.get('tdm', {})
+
+    if options.uav_id is None:
+        options.uav_id = int(cfg.get('uav_id', 0))
+    if options.slot_duration is None:
+        options.slot_duration = float(tdm_cfg.get('slot_duration', 0.5))
+    if options.guard_interval is None:
+        options.guard_interval = float(tdm_cfg.get('guard_interval', 0.05))
+    if options.num_uavs is None:
+        try:
+            options.num_uavs = derive_num_uavs_from_csv(
+                '/root/miSim/aerpaw/config/scenario.csv')
+        except Exception as e:
+            print(f"[TDM] Warning: could not derive num_uavs from scenario.csv: {e}")
+            print("[TDM] Defaulting to num_uavs=1 (TDM effectively disabled)")
+            options.num_uavs = 1
+
+    return options
+
+
+def main(top_block_cls=CSwSNRTX, options=None):
+    if options is None:
+        options = argument_parser().parse_args()
+
+    options = _resolve_tdm_options(options)
+
+    tb = top_block_cls(
+        args=options.args, freq=options.freq, gaintx=options.gaintx,
+        offset=options.offset, samp_rate=options.samp_rate, sps=options.sps,
+        uav_id=options.uav_id, num_uavs=options.num_uavs,
+        slot_duration=options.slot_duration,
+        guard_interval=options.guard_interval)
+
+    tdm_sched = TdmScheduler(
+        tb.blocks_mute_0,
+        uav_id=options.uav_id,
+        num_uavs=options.num_uavs,
+        slot_duration=options.slot_duration,
+        guard_interval=options.guard_interval)
+
+    def sig_handler(sig=None, frame=None):
+        tdm_sched.stop()
+        tb.stop()
+        tb.wait()
+        sys.exit(0)
+
+    signal.signal(signal.SIGINT, sig_handler)
+    signal.signal(signal.SIGTERM, sig_handler)
+
+    tb.start()
+    tdm_sched.start()
+
+    try:
+        input('Press Enter to quit: ')
+    except EOFError:
+        pass
+    tdm_sched.stop()
+    tb.stop()
+    tb.wait()
+
+
+if __name__ == '__main__':
+    main()
+(END)
+
+

aerpaw/radio/startchannelsounderRXGRC.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+GAIN_RX=30
+OFFSET=250e3
+SAMP_RATE=2e6
+SPS=16
+
+# Custom
+RX_FREQ=3.32e9
+
+if [ "$LAUNCH_MODE" == "TESTBED" ]; then
+  #To select a specific device
+  #ARGS="serial=31E74A9"
+  ARGS=NULL
+elif [ "$LAUNCH_MODE" == "EMULATION" ]; then
+  #ARGS='type=zmq'
+  ARGS=NULL
+else
+  echo "Warning: LAUNCH_MODE not set (got '${LAUNCH_MODE}'). Defaulting to TESTBED."
+  ARGS=NULL
+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 $SPS "$@"

aerpaw/radio/startchannelsounderTXGRC.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+GAIN_TX=76
+OFFSET=250e3
+SAMP_RATE=2e6
+SPS=16
+
+# Custom
+TX_FREQ=3.32e9
+
+if [ "$LAUNCH_MODE" == "TESTBED" ]; then
+  #To select a specific device
+  #ARGS="serial=31E74A9"
+  ARGS=NULL
+elif [ "$LAUNCH_MODE" == "EMULATION" ]; then
+  #ARGS='type=zmq'
+  ARGS=NULL
+else
+  echo "Warning: LAUNCH_MODE not set (got '${LAUNCH_MODE}'). Defaulting to TESTBED."
+  ARGS=NULL
+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 $SPS "$@"

aerpaw/radio/updateScripts.sh

@@ -0,0 +1,15 @@
+#!/bin/bash
+
+# Drop in replacements for channel sounder scripts
+cp startchannelsounderRXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
+cp startchannelsounderTXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
+cp CSwSNRRX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
+cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
+
+# Replace start scripts
+cp ../scripts/startexperiment.sh /root/.
+cp ../scripts/startRadio.sh /root/Profiles/ProfileScripts/Radio/.
+cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
+
+echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
+echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"

aerpaw/results/plotGpsCsvs.m

@@ -1,68 +0,0 @@
-% Plot setup
-f = uifigure;
-gf = geoglobe(f);
-hold(gf, "on");
-c = ["g", "b", "m", "c"]; % plotting colors
-
-% paths
-scenarioCsv = fullfile("aerpaw", "config", "scenario.csv");
-
-% configured data
-params = readScenarioCsv(scenarioCsv);
-
-% coordinate system constants
-seaToGroundLevel = 110; % meters, measured approximately from USGS national map viewer
-
-fID = fopen(fullfile("aerpaw", "config", "client.yaml"), 'r');
-yaml = fscanf(fID, '%s');
-fclose(fID);
-% origin (LLA)
-lla0 = [str2double(yaml((strfind(yaml, 'lat:') + 4):(strfind(yaml, 'lon:') - 1))), str2double(yaml((strfind(yaml, 'lon:') + 4):(strfind(yaml, 'alt:') - 1))), seaToGroundLevel];
-
-% Paths to logs
-gpsCsvs = dir(fullfile("sandbox", "test10", "*.csv"));
-
-G = cell(size(gpsCsvs));
-for ii = 1:size(gpsCsvs, 1)
-     % Read CSV
-    G{ii} = readGpsCsv(fullfile(gpsCsvs(ii).folder, gpsCsvs(ii).name));
-
-    % Find when algorithm begins/ends (using ENU altitude rate change)
-    enuTraj = lla2enu([G{ii}.Latitude, G{ii}.Longitude, G{ii}.Altitude], lla0, 'flat');
-
-    verticalSpeed = movmean(abs(diff(G{ii}.Altitude)), [10, 0]);
-
-    % Automatically detect start/stop of algorithm flight (ignore takeoff, setup, return to liftoff, landing segments of flight)
-    pctThreshold = 60; % pctThreshold may need adjusting depending on your flight
-    startIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, 'first'); 
-    stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, 'last');
-
-    % % Plot whole flight, including setup/cleanup
-    startIdx = 1;
-    stopIdx = length(verticalSpeed);
-    
-    % Plot recorded trajectory over specified range of indices
-    geoplot3(gf, G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx) + seaToGroundLevel, c(mod(ii, length(c))), 'LineWidth', 2, "MarkerSize", 5);
-end
-
-% Plot domain
-altOffset = 1; % to avoid clipping into the ground when displayed
-domain = [lla0; enu2lla(params.domainMax, lla0, 'flat')];
-geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(1, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'k');
-geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(2, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'k');
-geoplot3(gf, [domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
-geoplot3(gf, [domain(2, 1), domain(2, 1)], [domain(1, 2), domain(1, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
-geoplot3(gf, [domain(1, 1), domain(1, 1)], [domain(2, 2), domain(2, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
-geoplot3(gf, [domain(2, 1), domain(2, 1)], [domain(2, 2), domain(2, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
-
-% Plot floor (minimum altitude constraint)
-floorAlt = params.minAlt;
-geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(1, 3) + altOffset + floorAlt, 1, 5), 'LineWidth', 3, 'Color', 'r');
-
-% Plot objective
-objectivePos = [params.objectivePos, 0];
-llaObj = enu2lla(objectivePos, lla0, 'flat');
-geoplot3(gf, [llaObj(1), llaObj(1)], [llaObj(2), llaObj(2)], [llaObj(3), domain(2, 3)], 'LineWidth', 3, "Color", 'y');
-
-% finish
-hold(gf, "off");

aerpaw/results/plotGpsLogs.m

@@ -0,0 +1,97 @@
+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
+    end
+    arguments (Output)
+        f (1, 1) matlab.ui.Figure;
+        G cell;
+    end
+    % Plot setup
+    f = uifigure;
+    gf = geoglobe(f);
+    hold(gf, "on");
+    c = ["g", "b", "m", "c"]; % plotting colors
+    
+    % paths
+    scenarioCsv = fullfile(matlab.project.rootProject().RootFolder, "aerpaw", "config", "scenario.csv");
+    
+    % configured data
+    params = readScenarioCsv(scenarioCsv);
+    
+    fID = fopen(fullfile(matlab.project.rootProject().RootFolder, "aerpaw", "config", "client1.yaml"), 'r');
+    yaml = fscanf(fID, '%s');
+    fclose(fID);
+    % origin (LLA)
+    lla0 = [str2double(yaml((strfind(yaml, 'lat:') + 4):(strfind(yaml, 'lon:') - 1))), str2double(yaml((strfind(yaml, 'lon:') + 4):(strfind(yaml, 'alt:') - 1))), seaToGroundLevel];
+    
+    logDirs = dir(logDirs);
+    logDirs = logDirs(3:end);
+    logDirs = logDirs([logDirs.isdir] == 1);
+
+    G = cell(size(logDirs));
+    for ii = 1:size(logDirs, 1)
+        % Find GPS log CSV
+        gpsCsv = dir(fullfile(logDirs(ii).folder, logDirs(ii).name));
+        gpsCsv = gpsCsv(endsWith({gpsCsv(:).name}, "_gps_log.csv"));
+        gpsCsv = fullfile(gpsCsv.folder, gpsCsv.name);
+    
+        % Read GPS log CSV
+        G{ii} = readGpsLogs(gpsCsv);
+    
+        % Find when algorithm begins/ends (using ENU altitude rate change)
+        verticalSpeed = movmean(abs(diff(G{ii}.Altitude)), [10, 0]);
+    
+        % Automatically detect start/stop of algorithm flight (ignore takeoff, setup, return to liftoff, landing segments of flight)
+        pctThreshold = 60; % pctThreshold may need adjusting depending on your flight
+        startIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "first");
+        stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
+    
+        % % Plot whole flight, including setup/cleanup
+        % 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
+        enu = NaN(height(G{ii}), 3);
+        enu(startIdx:stopIdx, :) = lla2enu([G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx)], lla0, "flat");
+        enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
+        G{ii} = [G{ii}, enu];
+    
+        % Plot recorded trajectory over specified range of indices
+        geoplot3(gf, G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx) + seaToGroundLevel, c(mod(ii, length(c))), 'LineWidth', 2, "MarkerSize", 5);
+    end
+    
+    % Plot domain
+    altOffset = 1; % to avoid clipping into the ground when displayed
+    domain = [lla0; enu2lla(params.domainMax, lla0, "flat")];
+    geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(1, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'k');
+    geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(2, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'k');
+    geoplot3(gf, [domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
+    geoplot3(gf, [domain(2, 1), domain(2, 1)], [domain(1, 2), domain(1, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
+    geoplot3(gf, [domain(1, 1), domain(1, 1)], [domain(2, 2), domain(2, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
+    geoplot3(gf, [domain(2, 1), domain(2, 1)], [domain(2, 2), domain(2, 2)], domain(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'k');
+    
+    % Plot floor (minimum altitude constraint)
+    floorAlt = params.minAlt;
+    geoplot3(gf, [domain(1, 1), domain(2, 1), domain(2, 1), domain(1, 1), domain(1, 1)], [domain(1, 2), domain(1, 2), domain(2, 2), domain(2, 2), domain(1, 2)], repmat(domain(1, 3) + altOffset + floorAlt, 1, 5), 'LineWidth', 3, 'Color', 'r');
+    
+    % Plot objective
+    objectivePos = [params.objectivePos, 0];
+    llaObj = enu2lla(objectivePos, lla0, "flat");
+    geoplot3(gf, [llaObj(1), llaObj(1)], [llaObj(2), llaObj(2)], [llaObj(3), domain(2, 3)], 'LineWidth', 3, "Color", 'y');
+    
+    % Plot obstacles
+    for ii = 1:params.numObstacles
+        obstacle = enu2lla([params.obstacleMin((1 + (ii - 1) * 3):(ii * 3)); params.obstacleMax((1 + (ii - 1) * 3):(ii * 3))], lla0, "flat");
+        geoplot3(gf, [obstacle(1, 1), obstacle(2, 1), obstacle(2, 1), obstacle(1, 1), obstacle(1, 1)], [obstacle(1, 2), obstacle(1, 2), obstacle(2, 2), obstacle(2, 2), obstacle(1, 2)], repmat(obstacle(1, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'r');
+        geoplot3(gf, [obstacle(1, 1), obstacle(2, 1), obstacle(2, 1), obstacle(1, 1), obstacle(1, 1)], [obstacle(1, 2), obstacle(1, 2), obstacle(2, 2), obstacle(2, 2), obstacle(1, 2)], repmat(obstacle(2, 3) + altOffset, 1, 5), 'LineWidth', 3, 'Color', 'r');
+        geoplot3(gf, [obstacle(1, 1), obstacle(1, 1)], [obstacle(1, 2), obstacle(1, 2)], obstacle(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'r');
+        geoplot3(gf, [obstacle(2, 1), obstacle(2, 1)], [obstacle(1, 2), obstacle(1, 2)], obstacle(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'r');
+        geoplot3(gf, [obstacle(1, 1), obstacle(1, 1)], [obstacle(2, 2), obstacle(2, 2)], obstacle(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'r');
+        geoplot3(gf, [obstacle(2, 1), obstacle(2, 1)], [obstacle(2, 2), obstacle(2, 2)], obstacle(:, 3) + altOffset, 'LineWidth', 3, 'Color', 'r');
+    end
+    
+    % finish
+    hold(gf, "off");
+end

aerpaw/results/plotRadioLogs.m

@@ -0,0 +1,84 @@
+function [f, R] = plotRadioLogs(resultsPath)
+    arguments (Input)
+        resultsPath (1, 1) string;
+    end
+    arguments (Output)
+        f (1, 1) matlab.ui.Figure;
+        R cell;
+    end
+
+    logDirs = dir(resultsPath);
+    logDirs = logDirs(3:end);
+    logDirs = logDirs([logDirs.isdir] == 1);
+
+    R = cell(size(logDirs));
+    for ii = 1:size(logDirs, 1)
+        R{ii} = readRadioLogs(fullfile(logDirs(ii).folder, logDirs(ii).name));
+    end
+
+    % Discard rows where any non-NaN dB metric is below -200 (sentinel values)
+    for ii = 1:numel(R)
+        snr = R{ii}.SNR;
+        pwr = R{ii}.Power;
+        bad = (snr < -200 & ~isnan(snr)) | (pwr < -200 & ~isnan(pwr));
+        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)"];
+
+    f = figure;
+    tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
+
+    for mi = 1:numel(metricNames)
+        ax = nexttile(tl);
+        hold(ax, 'on');
+        grid(ax, 'on');
+
+        legendEntries = string.empty;
+        ci = 1;
+        for rxIdx = 1:nUAV
+            tbl = R{rxIdx};
+            txIDs = unique(tbl.TxUAVID);
+            for ti = 1:numel(txIDs)
+                txID = txIDs(ti);
+                rows = tbl(tbl.TxUAVID == txID, :);
+                vals = rows.(metricNames(mi));
+
+                % Skip if all NaN for this metric
+                if all(isnan(vals))
+                    continue;
+                end
+
+                si = mod(ci - 1, numel(styles)) + 1;
+                plot(ax, rows.Timestamp, vals, styles(si), ...
+                    'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
+                legendEntries(end+1) = sprintf("TX %d → RX %d", txID, tbl.RxUAVID(1)); %#ok<AGROW>
+                ci = ci + 1;
+            end
+        end
+
+        ylabel(ax, yLabels(mi));
+        if mi == numel(metricNames)
+            xlabel(ax, 'Time');
+        end
+        legend(ax, legendEntries, 'Location', 'best');
+        hold(ax, 'off');
+    end
+
+    title(tl, 'Radio Channel Metrics');
+end

aerpaw/results/readGpsCsv.m

@@ -1,33 +0,0 @@
-function [G] = readGpsCsv(csvPath)
-arguments (Input)
-    csvPath (1, 1) string {isfile(csvPath)};
-end
-
-arguments (Output)
-    G (:, 10) table;
-end
-
-G = readtable(csvPath, "ReadVariableNames", false);
-
-% first column is just index, meaningless, toss it
-G = G(:, 2:end);
-
-% switch to the correct LLA convention (lat, lon, alt)
-tmp = G(:, 2);
-G(:, 2) = G(:, 1);
-G(:, 1) = tmp;
-
-% Split pitch, yaw, roll data read in as one string per timestep into separate columns
-PYR = cell2mat(cellfun(@(x) str2num(strip(strip(x, "left", "("), "right", ")")), table2cell(G(:, 5)), "UniformOutput", false)); %#ok<ST2NM>
-% Reinsert to original table
-G = [G(:, 1:3), table(PYR(:, 1), VariableNames="Pitch"), table(PYR(:, 2), VariableNames="Yaw"), table(PYR(:, 3), VariableNames="Roll"), G(:, 6:end)];
-
-% Clean up datetime entry
-G = [table(datetime(G{:,8}, "InputFormat","yyyy-MM-dd HH:mm:ss.SSS", "TimeZone","America/New_York")), G(:, [1:7, 9:10])];
-
-% Fix variable names
-G.Properties.VariableNames = ["Timestamp", "Latitude", "Longitude", "Altitude", "Pitch", "Yaw", "Roll", "Voltage", "GPS Status", "Satellites"];
-G.Properties.VariableTypes = ["datetime", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
-G.Properties.VariableUnits = ["yyyy-MM-dd HH:mm:ss.SSS (UTC+5)", "deg", "deg", "m", "deg", "deg", "deg", "Volts", "", ""];
-
-end

aerpaw/results/readGpsLogs.m

@@ -0,0 +1,32 @@
+function [G] = readGpsLogs(logPath)
+    arguments (Input)
+        logPath (1, 1) string {isfile(logPath)};
+    end
+    
+    arguments (Output)
+        G (:, 10) table;
+    end
+    
+    G = readtable(logPath, "ReadVariableNames", false);
+    
+    % first column is just index, meaningless, toss it
+    G = G(:, 2:end);
+    
+    % switch to the correct LLA convention (lat, lon, alt)
+    tmp = G(:, 2);
+    G(:, 2) = G(:, 1);
+    G(:, 1) = tmp;
+    
+    % Split pitch, yaw, roll data read in as one string per timestep into separate columns
+    PYR = cell2mat(cellfun(@(x) str2num(strip(strip(x, "left", "("), "right", ")")), table2cell(G(:, 5)), "UniformOutput", false)); %#ok<ST2NM>
+    % Reinsert to original table
+    G = [G(:, 1:3), table(PYR(:, 1), VariableNames="Pitch"), table(PYR(:, 2), VariableNames="Yaw"), table(PYR(:, 3), VariableNames="Roll"), G(:, 6:end)];
+    
+    % Clean up datetime entry
+    G = [table(datetime(G{:,8}, "InputFormat","yyyy-MM-dd HH:mm:ss.SSS", "TimeZone","America/New_York")), G(:, [1:7, 9:10])];
+    
+    % Fix variable names
+    G.Properties.VariableNames = ["Timestamp", "Latitude", "Longitude", "Altitude", "Pitch", "Yaw", "Roll", "Voltage", "GPS Status", "Satellites"];
+    G.Properties.VariableTypes = ["datetime", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+    G.Properties.VariableUnits = ["yyyy-MM-dd HH:mm:ss.SSS (UTC+5)", "deg", "deg", "m", "deg", "deg", "deg", "Volts", "", ""];
+end

aerpaw/results/readRadioLogs.m

@@ -0,0 +1,67 @@
+function R = readRadioLogs(logPath)
+    arguments (Input)
+        logPath (1, 1) string {isfolder(logPath)};
+    end
+
+    arguments (Output)
+        R (:, 8) 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"];
+    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"]);
+
+    for ii = 1:numel(logs)
+        filepath = fullfile(logs(ii).folder, logs(ii).name);
+
+        % Determine which metric this file contains
+        metric = "";
+        for m = 1:numel(metrics)
+            if endsWith(logs(ii).name, metrics(m) + "_log.txt")
+                metric = metrics(m);
+                break;
+            end
+        end
+
+        fid = fopen(filepath, 'r');
+        % 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(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"]);
+
+        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>
+    end
+
+    R = sortrows(R, "Timestamp");
+
+    % Remove rows during defined guard period between TDM shifts
+    R(R.TxUAVID == -1, :) = [];
+
+    % Remove self-reception rows (TX == RX)
+    R(R.TxUAVID == R.RxUAVID, :) = [];
+end

aerpaw/results/resultsAnalysis.m

@@ -0,0 +1,68 @@
+%% Plot AERPAW logs (trajectory, radio)
+resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % 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
+[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
+
+% Plot radio statistics
+[fRadio, R] = plotRadioLogs(resultsPath);
+
+%% Run simulation
+% Run miSim using same AERPAW scenario definition CSV
+csvPath = fullfile(matlab.project.rootProject().RootFolder, "aerpaw", "config", "scenario.csv");
+params = readScenarioCsv(csvPath);
+
+% Visualization settings
+plotCommsGeometry = false;
+makePlots = true;
+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, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
+
+agents = cell(size(params.initialPositions, 2) / 3, 1);
+for ii = 1:size(agents, 1)
+    agents{ii} = agent;
+
+    sensorModel = sigmoidSensor;
+    sensorModel = sensorModel.initialize(params.alphaDist(ii), params.betaDist(ii), params.alphaTilt(ii), params.betaTilt(ii));
+
+    collisionGeometry = spherical;
+    collisionGeometry = collisionGeometry.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), params.collisionRadius(ii), REGION_TYPE.COLLISION, sprintf("Agent %d collision geometry", ii));
+
+    agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, sprintf("Agent %d", ii), plotCommsGeometry);
+end
+
+% Create obstacles
+obstacles = cell(params.numObstacles, 1);
+for ii = 1:size(obstacles, 1)
+    obstacles{ii} = rectangularPrism;
+    obstacles{ii} = obstacles{ii}.initialize([params.obstacleMin((((ii - 1) * 3) + 1):(ii * 3)); params.obstacleMax((((ii - 1) * 3) + 1):(ii * 3))], "OBSTACLE", sprintf("Obstacle %d", ii));
+end
+
+% Set up simulation
+sim = miSim;
+sim = sim.initialize(domain, agents, params.barrierGain, params.barrierExponent, params.minAlt, params.timestep, params.maxIter, obstacles, makePlots, makeVideo);
+
+% Save simulation parameters to output file
+sim.writeInits();
+
+% Run
+sim = sim.run();
+
+%% Plot AERPAW trajectory logs onto simulated result for comparison
+% Duplicate plot to overlay with logged trajectories
+comparison = figure;
+copyobj(sim.f.Children, comparison);
+
+% Plot trajectories on top
+for ii = 1:size(G, 1)
+    for jj = 1:size(sim.spatialPlotIndices, 2)
+        hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "on");
+        plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East, G{ii}.North, G{ii}.Up + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
+        hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "off");
+    end
+end

aerpaw/run_uav.sh

@@ -3,13 +3,13 @@
 # Launches UAV client with environment-specific configuration
 #
 # Usage:
-#   ./run_uav.sh local     # Use local/simulation configuration
+#   ./run_uav.sh local                          # defaults to config/client.yaml
-#   ./run_uav.sh testbed   # Use AERPAW testbed configuration
+#   ./run_uav.sh testbed config/client2.yaml     # use a specific config file
 
 set -e
 
-# Change to script directory
+# Change to aerpaw directory
-cd "$(dirname "$0")"
+cd /root/miSim/aerpaw
 
 # Activate venv if it exists
 if [ -d "venv" ]; then
@@ -23,22 +23,33 @@ elif [ "$1" = "local" ]; then
     ENV="local"
 else
     echo "Error: Environment not specified."
-    echo "Usage: $0 [local|testbed]"
+    echo "Usage: $0 [local|testbed] [config_file]"
     echo ""
     echo "  local   - Use local/simulation configuration"
     echo "  testbed - Use AERPAW testbed configuration"
+    echo ""
+    echo "  config_file - Path to client YAML (default: config/client.yaml)"
+    exit 1
+fi
+
+# Client config file: 2nd argument > AERPAW_CLIENT_CONFIG env var > default
+CONFIG_FILE="${2:-${AERPAW_CLIENT_CONFIG:-config/client.yaml}}"
+if [ ! -f "$CONFIG_FILE" ]; then
+    echo "Error: Config file not found: $CONFIG_FILE"
     exit 1
 fi
 
 echo "[run_uav] Environment: $ENV"
+echo "[run_uav] Config file: $CONFIG_FILE"
 
-# Export environment for Python to use
+# Export for Python scripts to use
 export AERPAW_ENV="$ENV"
+export AERPAW_CLIENT_CONFIG="$(realpath "$CONFIG_FILE")"
 
-# Read MAVLink connection from config.yaml using Python
+# Read MAVLink connection from config file using Python
 CONN=$(python3 -c "
 import yaml
-with open('config/client.yaml') as f:
+with open('$CONFIG_FILE') as f:
     cfg = yaml.safe_load(f)
 env = cfg['environments']['$ENV']['mavlink']
 print(f\"udp:{env['ip']}:{env['port']}\")
@@ -48,7 +59,7 @@ echo "[run_uav] MAVLink connection: $CONN"
 
 # Run via aerpawlib
 echo "[run_uav] Starting UAV runner..."
-python3 -m aerpawlib \
+python3 -u -m aerpawlib \
     --script client.uav_runner \
     --conn "$CONN" \
     --vehicle drone

aerpaw/scripts/startRadio.sh

@@ -0,0 +1,100 @@
+#!/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

@@ -0,0 +1,30 @@
+#!/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

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

aerpaw/scripts/startexperiment.sh

@@ -0,0 +1,50 @@
+#!/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

@@ -0,0 +1,47 @@
+#!/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

plots_1_2.m

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

plots_3_4.m

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

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