a

@agent/agent.m

@@ -1,16 +1,12 @@
 classdef agent
-    properties (SetAccess = private, GetAccess = public)
+    properties (SetAccess = public, GetAccess = public)
         % Identifiers
-        index = NaN;
         label = "";
 
         % Sensor
         sensorModel;
         sensingLength = 0.05; % length parameter used by sensing function
 
-        % Guidance
-        guidanceModel;
-
         % State
         lastPos = NaN(1, 3); % position from previous timestep
         pos = NaN(1, 3); % current position
@@ -20,20 +16,29 @@ classdef agent
 
         % Collision
         collisionGeometry;
+        barrierFunction;
+        dBarrierFunction;
 
         % FOV cone
         fovGeometry;
 
         % Communication
         comRange = NaN;
+        commsGeometry = spherical;
+        lesserNeighbors = [];
+
+        performance = 0;
 
         % Plotting
         scatterPoints;
+        debug = false;
+        debugFig;
+        plotCommsGeometry = true;
     end
 
     methods (Access = public)
         [obj] = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
-        [obj] = run(obj, sensingObjective, domain, partitioning);
+        [obj] = run(obj, domain, partitioning, t, index);
         [obj, f] = plot(obj, ind, f);
         updatePlots(obj);
     end

@agent/initialize.m

@@ -1,4 +1,4 @@
-function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label)
+function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, comRange, label, debug, plotCommsGeometry)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, 'agent')};
         pos (1, 3) double;
@@ -6,11 +6,11 @@ function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorMod
         pan (1, 1) double;
         tilt (1, 1) double;
         collisionGeometry (1, 1) {mustBeGeometry};
-        sensorModel (1, 1) {mustBeSensor}
-        guidanceModel (1, 1) {mustBeA(guidanceModel, 'function_handle')};
-        comRange (1, 1) double = NaN;
-        index (1, 1) double = NaN;
+        sensorModel (1, 1) {mustBeSensor};
+        comRange (1, 1) double;
         label (1, 1) string = "";
+        debug (1, 1) logical = false;
+        plotCommsGeometry (1, 1) logical = false;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, 'agent')};
@@ -22,10 +22,57 @@ function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorMod
     obj.tilt = tilt;
     obj.collisionGeometry = collisionGeometry;
     obj.sensorModel = sensorModel;
-    obj.guidanceModel = guidanceModel;
-    obj.comRange = comRange;
-    obj.index = index;
     obj.label = label;
+    obj.debug = debug;
+    obj.plotCommsGeometry = plotCommsGeometry;
+
+    % Add spherical geometry based on com range
+    obj.commsGeometry = obj.commsGeometry.initialize(obj.pos, comRange, REGION_TYPE.COMMS, sprintf("%s Comms Geometry", obj.label));
+
+    if obj.debug
+        obj.debugFig = figure;
+        tiledlayout(obj.debugFig, "TileSpacing", "tight", "Padding", "compact");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Objective");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Sensor Performance");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Gradient Objective");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Gradient Sensor Performance");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Sensor Performance x Gradient Objective");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Gradient Sensor Performance x Objective");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Agent Performance (C)");
+        nexttile;
+        axes(obj.debugFig.Children(1).Children(1));
+        axis(obj.debugFig.Children(1).Children(1), "image");
+        xlabel(obj.debugFig.Children(1).Children(1), "X"); ylabel(obj.debugFig.Children(1).Children(1), "Y");
+        title(obj.debugFig.Children(1).Children(1), "Gradient Agent Performance (del C)");
+    end
 
     % Initialize FOV cone
     obj.fovGeometry = cone;

@agent/plot.m

@@ -30,6 +30,11 @@ function [obj, f] = plot(obj, ind, f)
     % Plot collision geometry
     [obj.collisionGeometry, f] = obj.collisionGeometry.plotWireframe(ind, f);
 
+    % Plot communications geometry
+    if obj.plotCommsGeometry
+        [obj.commsGeometry, f] = obj.commsGeometry.plotWireframe(ind, f);
+    end
+
     % Plot FOV geometry
     [obj.fovGeometry, f] = obj.fovGeometry.plot(ind, f);
 end

@agent/run.m

@@ -1,28 +1,155 @@
-function obj = run(obj, sensingObjective, domain, partitioning)
+function obj = run(obj, domain, partitioning, t, index)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, 'agent')};
-        sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
         domain (1, 1) {mustBeGeometry};
         partitioning (:, :) double;
+        t (1, 1) double;
+        index (1, 1) double;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, 'agent')};
     end
 
-    % Do sensing
-    [sensedValues, sensedPositions] = obj.sensorModel.sense(obj, sensingObjective, domain, partitioning);
+    % Collect objective function values across partition
+    partitionMask = partitioning == index;
+    objectiveValues = domain.objective.values(partitionMask); % f(omega) on W_n
 
-    % Determine next planned position
-    nextPos = obj.guidanceModel(sensedValues, sensedPositions, obj.pos);
+    % Compute sensor performance across partition
+    maskedX = domain.objective.X(partitionMask);
+    maskedY = domain.objective.Y(partitionMask);
+    zFactor = 1;
+    sensorValues = obj.sensorModel.sensorPerformance(obj.pos, obj.pan, obj.tilt, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
+    sensorValuesLower = obj.sensorModel.sensorPerformance(obj.pos - [0, 0, zFactor * domain.objective.discretizationStep], obj.pan, obj.tilt, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n - [0, 0, z]) on W_n
+    sensorValuesHigher = obj.sensorModel.sensorPerformance(obj.pos + [0, 0, zFactor * domain.objective.discretizationStep], obj.pan, obj.tilt, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n - [0, 0, z]) on W_n
+
+    % Put the values back into the form of the partition to enable basic operations on this data
+    F = NaN(size(partitionMask));
+    F(partitionMask) = objectiveValues;
+    S = NaN(size(partitionMask));
+    Slower = S;
+    Shigher = S;
+    S(partitionMask) = sensorValues;
+    Slower(partitionMask) = sensorValuesLower;
+    Shigher(partitionMask) = sensorValuesHigher;
+
+    % Find agent's performance
+    C = S .* F;
+    obj.performance = [obj.performance, sum(C(~isnan(C)))]; % at current Z only
+    C = cat(3, Shigher, S, Slower) .* F;
+
+    % Compute gradient on agent's performance
+    [gradCX, gradCY, gradCZ] = gradient(C, domain.objective.discretizationStep); % grad C
+    gradC = cat(4, gradCX, gradCY, gradCZ);
+    nGradC = vecnorm(gradC, 2, 4);
+
+    if obj.debug
+        % Compute additional component-level values for diagnosing issues
+        [gradSensorPerformanceX, gradSensorPerformanceY] = gradient(S, domain.objective.discretizationStep); % grad S_n
+        [gradObjectiveX, gradObjectiveY] = gradient(F, domain.objective.discretizationStep); % grad f
+        gradS = cat(3, gradSensorPerformanceX, gradSensorPerformanceY, zeros(size(gradSensorPerformanceX))); % grad S_n
+        gradF = cat(3, gradObjectiveX, gradObjectiveY, zeros(size(gradObjectiveX))); % grad f
+
+        ii = 8;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), F./max(F, [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), S./max(S, [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), vecnorm(gradF, 2, 3)./max(vecnorm(gradF, 2, 3), [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), vecnorm(gradS, 2, 3)./max(vecnorm(gradS, 2, 3), [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), S .* vecnorm(gradF, 2, 3)./max(vecnorm(gradF, 2, 3), [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), F .* vecnorm(gradS, 2, 3)./max(vecnorm(gradS, 2, 3), [], 'all')./(max(F .* vecnorm(gradS, 2, 3)./max(vecnorm(gradS, 2, 3), [], 'all'))));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), C./max(C, [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        ii = ii - 1;
+        hold(obj.debugFig.Children(1).Children(ii), "on");
+        cla(obj.debugFig.Children(1).Children(ii));
+        imagesc(obj.debugFig.Children(1).Children(ii), nGradC./max(nGradC, [], 'all'));
+        hold(obj.debugFig.Children(1).Children(ii), "off");
+        [x, y] = find(nGradC == max(nGradC, [], "all"));
+
+        % just pick one
+        r = randi([1, size(x, 1)]);
+        x = x(r); y = y(r);
+
+        % switch them
+        temp = x;
+        x = y;
+        y = temp;
+        
+        % find objective location in discrete domain
+        [~, xIdx] = find(domain.objective.groundPos(1) == domain.objective.X);
+        xIdx = unique(xIdx);
+        [yIdx, ~] = find(domain.objective.groundPos(2) == domain.objective.Y);
+        yIdx = unique(yIdx);
+        for ii = 8:-1:1
+            hold(obj.debugFig.Children(1).Children(ii), "on");
+            % plot GA selection
+            scatter(obj.debugFig.Children(1).Children(ii), x, y, 'go');
+            scatter(obj.debugFig.Children(1).Children(ii), x, y, 'g+');
+            % plot objective center
+            scatter(obj.debugFig.Children(1).Children(ii), xIdx, yIdx, 'ro');
+            scatter(obj.debugFig.Children(1).Children(ii), xIdx, yIdx, 'r+');
+            hold(obj.debugFig.Children(1).Children(ii), "off");
+        end
+    end
+
+    % return now if there is no data to work with, and do not move
+    if all(isnan(nGradC), 'all')
+        return;
+    end
+
+    % Use largest grad(C) value to find the direction of the next position
+    [xNextIdx, yNextIdx, zNextIdx] = ind2sub(size(nGradC), find(nGradC == max(nGradC, [], 'all')));
+    % switch them
+    temp = xNextIdx;
+    xNextIdx = yNextIdx;
+    yNextIdx = temp;
+
+    roundingScale = 10^-log10(domain.objective.discretizationStep);
+    zKey = zFactor * [1; 0; -1];
+    pNext = [floor(roundingScale .* mean(unique(domain.objective.X(:, xNextIdx))))./roundingScale, floor(roundingScale .* mean(unique(domain.objective.Y(yNextIdx, :))))./roundingScale, obj.pos(3) + zKey(zNextIdx)]; % have to do some unfortunate rounding here sometimes
+
+    % Determine next position
+    vDir = (pNext - obj.pos)./norm(pNext - obj.pos, 2);
+    rate = 0.1 - 0.0004 * t; % slow down as you get closer, coming to a stop by the end
+    nextPos = obj.pos + vDir * rate;
 
     % Move to next position
-    % (dynamics not modeled at this time)
     obj.lastPos = obj.pos;
     obj.pos = nextPos;
 
-    % Calculate movement
-    d = obj.pos - obj.collisionGeometry.center;
-
     % Reinitialize collision geometry in the new position
+    d = obj.pos - obj.collisionGeometry.center;
+    if isa(obj.collisionGeometry, 'rectangularPrism')
         obj.collisionGeometry = obj.collisionGeometry.initialize([obj.collisionGeometry.minCorner; obj.collisionGeometry.maxCorner] + d, obj.collisionGeometry.tag, obj.collisionGeometry.label);
+    elseif isa(obj.collisionGeometry, 'spherical')
+        obj.collisionGeometry = obj.collisionGeometry.initialize(obj.collisionGeometry.center + d, obj.collisionGeometry.radius, obj.collisionGeometry.tag, obj.collisionGeometry.label);
+    else
+        error("?");
+    end
 end

@agent/updatePlots.m

@@ -25,6 +25,17 @@ function updatePlots(obj)
         end
     end
 
+    % Communications geometry edges
+    if obj.plotCommsGeometry
+        for jj = 1:size(obj.commsGeometry.lines, 2)
+            for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
+                obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
+                obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
+                obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
+            end
+        end
+    end
+
     % Update FOV geometry surfaces
     for jj = 1:size(obj.fovGeometry.surface, 2)
         % Update each plot

@miSim/constrainMotion.m

@@ -0,0 +1,153 @@
+function [obj] = constrainMotion(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+
+    if size(obj.agents, 1) < 2
+        nAAPairs = 0;
+    else
+        nAAPairs = nchoosek(size(obj.agents, 1), 2); % unique agent/agent pairs
+    end
+
+    agents = [obj.agents{:}];
+    v = reshape(([agents.pos] - [agents.lastPos])./obj.timestep, 3, size(obj.agents, 1))';
+
+    % Initialize QP based on number of agents and obstacles
+    nAOPairs = size(obj.agents, 1) * size(obj.obstacles, 1); % unique agent/obstacle pairs
+    nADPairs = size(obj.agents, 1) * 5; % agents x (4 walls + 1 ceiling)
+    nLNAPairs = sum(obj.constraintAdjacencyMatrix, 'all') - size(obj.agents, 1);
+    total = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
+    kk = 1;
+    A = zeros(total, 3 * size(obj.agents, 1));
+    b = zeros(total, 1);
+
+    % Set up collision avoidance constraints
+    h = NaN(size(obj.agents, 1));
+    h(logical(eye(size(obj.agents, 1)))) = 0; % self value is 0
+    for ii = 1:(size(obj.agents, 1) - 1)
+        for jj = (ii + 1):size(obj.agents, 1)
+            h(ii, jj) = norm(agents(ii).pos - agents(jj).pos)^2 - (agents(ii).collisionGeometry.radius + agents(jj).collisionGeometry.radius)^2;
+            h(jj, ii) = h(ii, jj);
+            
+            A(kk, (3 * ii - 2):(3 * ii)) =  -2 * (agents(ii).pos - agents(jj).pos);
+            A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
+            b(kk) = obj.barrierGain * h(ii, jj)^3;
+            kk = kk + 1;
+        end
+    end
+
+    hObs = NaN(size(obj.agents, 1), size(obj.obstacles, 1));
+    % Set up obstacle avoidance constraints
+    for ii = 1:size(obj.agents, 1)
+        for jj = 1:size(obj.obstacles, 1)
+            % find closest position to agent on/in obstacle
+            cPos = obj.obstacles{jj}.closestToPoint(agents(ii).pos);
+
+            hObs(ii, jj) = dot(agents(ii).pos - cPos, agents(ii).pos - cPos) - agents(ii).collisionGeometry.radius^2;
+
+            A(kk, (3 * ii - 2):(3 * ii)) = -2 * (agents(ii).pos - cPos);
+            b(kk) = obj.barrierGain * hObs(ii, jj)^3;
+           
+            kk = kk + 1;
+        end
+    end
+    
+    % 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
+    for ii = 1:size(obj.agents, 1)
+        % X minimum
+        h_xMin = (agents(ii).pos(1) - obj.domain.minCorner(1)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
+        b(kk) = obj.barrierGain * h_xMin^3;
+        kk = kk + 1;
+    
+        % X maximum
+        h_xMax = (obj.domain.maxCorner(1) - agents(ii).pos(1)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
+        b(kk) = obj.barrierGain * h_xMax^3;
+        kk = kk + 1;
+    
+        % Y minimum
+        h_yMin = (agents(ii).pos(2) - obj.domain.minCorner(2)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
+        b(kk) = obj.barrierGain * h_yMin^3;
+        kk = kk + 1;
+    
+        % Y maximum
+        h_yMax = (obj.domain.maxCorner(2) - agents(ii).pos(2)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
+        b(kk) = obj.barrierGain * h_yMax^3;
+        kk = kk + 1;
+    
+        % Z minimum
+        h_zMin = (agents(ii).pos(3) - obj.domain.minCorner(3)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
+        b(kk) = obj.barrierGain * h_zMin^3;
+        kk = kk + 1;
+    
+        % Z maximum
+        h_zMax = (obj.domain.maxCorner(2) - agents(ii).pos(2)) - agents(ii).collisionGeometry.radius;
+        A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
+        b(kk) = obj.barrierGain * h_zMax^3;
+        kk = kk + 1;
+    end
+
+    % Save off h function values (ignoring network constraints which may evolve in time)
+    obj.h(:, obj.timestepIndex) = [h(triu(true(size(obj.agents, 1)), 1)); reshape(hObs, [], 1); h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax;]; 
+
+    % Add communication network constraints
+    hComms = NaN(size(obj.agents, 1));
+    hComms(logical(eye(size(obj.agents, 1)))) = 0;
+    for ii = 1:(size(obj.agents, 1) - 1)
+        for jj = (ii + 1):size(obj.agents, 1)
+            if obj.constraintAdjacencyMatrix(ii, jj)
+                hComms(ii, jj) = min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])^2 - norm(agents(ii).pos - agents(jj).pos)^2;
+
+                A(kk, (3 * ii - 2):(3 * ii)) =  2 * (agents(ii).pos - agents(jj).pos);
+                A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
+                b(kk) = obj.barrierGain * hComms(ii, jj);
+
+                % dVNominal = v(ii, 1:3) - v(jj, 1:3); % nominal velocities
+                % h_dot_nom = -2 * (agents(ii).pos - agents(jj).pos) * dVNominal';
+                % b(kk) = -h_dot_nom + obj.barrierGain * hComms(ii, jj)^3;
+
+                kk = kk + 1; 
+            end
+        end
+    end
+
+    % Solve QP program generated earlier
+    vhat = reshape(v', 3 * size(obj.agents, 1), 1);
+    H = 2 * eye(3 * size(obj.agents, 1));
+    f = -2 * vhat;
+    
+    % Update solution based on constraints
+    assert(size(A,2) == size(H,1))
+    assert(size(A,1) == size(b,1))
+    assert(size(H,1) == length(f))
+    opt = optimoptions('quadprog', 'Display', 'off');
+    [vNew, ~, exitflag, m] = quadprog(sparse(H), double(f), A, b, [],[], [], [], [], opt);
+    assert(exitflag == 1, sprintf('quadprog failure... %s%s', newline, m.message));
+    vNew = reshape(vNew, 3, size(obj.agents, 1))';
+
+    if exitflag <= 0
+        warning("QP failed, continuing with unconstrained solution...")
+        vNew = v;
+    end
+
+    % Update the "next position" that was previously set by unconstrained
+    % GA using the constrained solution produced here
+    for ii = 1:size(vNew, 1)
+        obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
+    end
+
+    % Here we run this at the simulation level, but in reality there is no
+    % parent level, so this would be run independently on each agent.
+    % Running at the simulation level is just meant to simplify the
+    % simulation
+
+end

@miSim/initialize.m

@@ -1,20 +1,34 @@
-function obj = initialize(obj, domain, objective, agents, timestep, partitoningFreq, maxIter, obstacles)
+function obj = initialize(obj, domain, objective, agents, minAlt, timestep, partitoningFreq, maxIter, obstacles, makePlots, makeVideo)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, 'miSim')};
         domain (1, 1) {mustBeGeometry};
         objective (1, 1) {mustBeA(objective, 'sensingObjective')};
         agents (:, 1) cell;
+        minAlt (1, 1) double = 1;
         timestep (:, 1) double = 0.05;
         partitoningFreq (:, 1) double = 0.25
         maxIter (:, 1) double = 1000;
         obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
+        makePlots(1, 1) logical = true;
+        makeVideo (1, 1) logical = true;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, 'miSim')};
     end
 
+    % enable/disable plotting and video writer
+    obj.makePlots = makePlots;
+    if ~obj.makePlots
+        if makeVideo
+            warning("makeVideo set to true, but makePlots set to false. Setting makeVideo to false.");
+            makeVideo = false;
+        end
+    end
+    obj.makeVideo = makeVideo;
+
     % Define simulation time parameters
     obj.timestep = timestep;
+    obj.timestepIndex = 0;
     obj.maxIter = maxIter - 1;
 
     % Define domain
@@ -24,26 +38,56 @@ function obj = initialize(obj, domain, objective, agents, timestep, partitoningF
     % Add geometries representing obstacles within the domain
     obj.obstacles = obstacles;
 
+    % Add an additional obstacle spanning the domain's footprint to 
+    % represent the minimum allowable altitude
+    obj.minAlt = minAlt;
+    if obj.minAlt > 0
+        obj.obstacles{end + 1, 1} = rectangularPrism;
+        obj.obstacles{end, 1} = obj.obstacles{end, 1}.initialize([obj.domain.minCorner; obj.domain.maxCorner(1:2), obj.minAlt], "OBSTACLE", "Minimum Altitude Domain Constraint");
+    end
+
     % Define objective
     obj.objective = objective;
 
     % Define agents
     obj.agents = agents;
+    obj.constraintAdjacencyMatrix = logical(eye(size(agents, 1)));
 
-    % Compute adjacency matrix
+    % Set labels for agents and collision geometries in cases where they
+    % were not provieded at the time of their initialization
+    for ii = 1:size(obj.agents, 1)
+        % Agent
+        if isempty(char(obj.agents{ii}.label))
+            obj.agents{ii}.label = sprintf("Agent %d", ii);
+        end
+
+        % Collision geometry
+        if isempty(char(obj.agents{ii}.collisionGeometry.label))
+            obj.agents{ii}.collisionGeometry.label = sprintf("Agent %d Collision Geometry", ii);
+        end
+    end
+
+    % Compute adjacency matrix and lesser neighbors
     obj = obj.updateAdjacency();
+    obj = obj.lesserNeighbor();
 
     % Set up times to iterate over
     obj.times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
     obj.partitioningTimes = obj.times(obj.partitioningFreq:obj.partitioningFreq:size(obj.times, 1));
 
     % Prepare performance data store (at t = 0, all have 0 performance)
-    obj.fPerf = figure;
     obj.perf = [zeros(size(obj.agents, 1) + 1, 1), NaN(size(obj.agents, 1) + 1, size(obj.partitioningTimes, 1) - 1)];
 
+    % Prepare h function data store
+    obj.h = NaN(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2 + size(obj.agents, 1) * size(obj.obstacles, 1) + 6, size(obj.times, 1) - 1);
+
     % Create initial partitioning
     obj = obj.partition();
 
+    % 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);
+
     % Set up plots showing initialized state
     obj = obj.plot();
 end

@miSim/lesserNeighbor.m

@@ -0,0 +1,76 @@
+function obj = lesserNeighbor(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+
+    % initialize solution with self-connections only
+    constraintAdjacencyMatrix = logical(eye(size(obj.agents, 1)));
+
+    for ii = 1:size(obj.agents, 1)
+        % Find lesser neighbors of each agent
+        % Lesser neighbors of ii are jj < ii in range of ii
+        lesserNeighbors = [];
+        for jj = 1:(ii - 1)
+            if obj.adjacency(ii, jj)
+                lesserNeighbors = [lesserNeighbors, jj];
+            end
+        end
+        obj.agents{ii}.lesserNeighbors = lesserNeighbors;
+        
+        % Early exit for isolated agents
+        if isempty(obj.agents{ii}.lesserNeighbors)
+            continue
+        end
+
+        % Focus on subgraph defined by lesser neighbors
+        subgraphAdjacency = obj.adjacency(obj.agents{ii}.lesserNeighbors, obj.agents{ii}.lesserNeighbors);
+
+        % Find connected components in each agent's subgraph
+        % TODO: rewrite this using matlab "conncomp" function?
+        visited = false(size(subgraphAdjacency, 1), 1);
+        components = {};
+        for jj = 1:size(subgraphAdjacency, 1)
+            if ~visited(jj)
+                reachable = bfs(subgraphAdjacency, jj);
+                visited(reachable) = true;
+                components{end+1} = obj.agents{ii}.lesserNeighbors(reachable);
+            end
+        end
+
+        % Connect to the greatest index in each connected component in the
+        % lesser neighborhood of this agent
+        for jj = 1:size(components, 2)
+            constraintAdjacencyMatrix(ii, max(components{jj})) = true;
+            constraintAdjacencyMatrix(max(components{jj}), ii) = true;
+        end
+    end
+    obj.constraintAdjacencyMatrix = constraintAdjacencyMatrix | constraintAdjacencyMatrix';
+end
+
+function cComp = bfs(subgraphAdjacency, startIdx)
+    n = size(subgraphAdjacency, 1);
+    visited = false(1, n);
+    queue = startIdx;
+    cComp = startIdx;
+    visited(startIdx) = true;
+    
+    while ~isempty(queue)
+        current = queue(1);
+        queue(1) = [];
+        
+        % Find all neighbors of current node in the subgraph
+        neighbors = find(subgraphAdjacency(current, :));
+        
+        for neighbor = neighbors
+            if ~visited(neighbor)
+                visited(neighbor) = true;
+                cComp = [cComp, neighbor];
+                queue = [queue, neighbor];
+            end
+        end
+    end
+    cComp = sort(cComp);
+end

@miSim/miSim.m

@@ -4,6 +4,7 @@ classdef miSim
     % Simulation parameters
     properties (SetAccess = private, GetAccess = public)
         timestep = NaN; % delta time interval for simulation iterations
+        timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
         partitioningFreq = NaN; % number of simulation timesteps at which the partitioning routine is re-run
         maxIter = NaN; % maximum number of simulation iterations
         domain = rectangularPrism;
@@ -11,10 +12,13 @@ classdef miSim
         obstacles = cell(0, 1); % geometries that define obstacles within the domain
         agents = cell(0, 1); % agents that move within the domain
         adjacency = NaN; % Adjacency matrix representing communications network graph
+        constraintAdjacencyMatrix = NaN; % Adjacency matrix representing desired lesser neighbor connections
         sensorPerformanceMinimum = 1e-6; % minimum sensor performance to allow assignment of a point in the domain to a partition
         partitioning = NaN;
-        performance = NaN; % current cumulative sensor performance
-        oldMeanTotalPerf = 0;
+        perf; % sensor performance timeseries array
+        performance = 0; % simulation performance timeseries vector
+        barrierGain = 100; % collision avoidance parameter
+        minAlt = 1; % minimum allowed altitude constraint
 
         fPerf; % performance plot figure
     end
@@ -22,35 +26,50 @@ classdef miSim
     properties (Access = private)
         % Sim
         t = NaN; % current sim time
-        perf; % sensor performance timeseries array
         times;
         partitioningTimes;
 
         % Plot objects
-        f = firstPlotSetup(); % main plotting tiled layout figure
+        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
+        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;
+
+        % CBF plotting
+        h; % h function values
+        hf; % h function plotting figure
+        caPlot; % objects for collision avoidance h function plot
+        obsPlot; % objects for obstacle h function plot
+        domPlot; % objects for domain h function plot
     end
 
     methods (Access = public)
         [obj] = initialize(obj, domain, objective, agents, timestep, partitoningFreq, maxIter, obstacles);
         [obj] = run(obj);
+        [obj] = lesserNeighbor(obj);
+        [obj] = constrainMotion(obj);
         [obj] = partition(obj);
         [obj] = updateAdjacency(obj);
         [obj] = plot(obj);
         [obj] = plotConnections(obj);
         [obj] = plotPartitions(obj);
         [obj] = plotGraph(obj);
+        [obj] = plotTrails(obj);
+        [obj] = plotH(obj);
         [obj] = updatePlots(obj, updatePartitions);
+        validate(obj);
     end
     methods (Access = private)
         [v] = setupVideoWriter(obj);

@miSim/partition.m

@@ -16,7 +16,13 @@ function obj = partition(obj)
     [~, idx] = max(agentPerformances, [], 3);
 
     % Collect agent indices in the same way as performance
-    agentInds = cellfun(@(x) x.index * ones(size(obj.objective.X)), obj.agents, 'UniformOutput', false);
+    indices = 1:size(obj.agents, 1);
+    agentInds = squeeze(tensorprod(indices, ones(size(obj.objective.X))));
+    if size(agentInds, 1) ~= size(obj.agents, 1)
+        agentInds = reshape(agentInds, [size(obj.agents, 1), size(agentInds)]); % needed for cases with 1 agent where prior squeeze is too agressive
+    end
+    agentInds = num2cell(agentInds, 2:3);
+    agentInds = cellfun(@(x) squeeze(x), agentInds, 'UniformOutput', false);
     agentInds{end + 1} = zeros(size(agentInds{end})); % index for no assignment
     agentInds = cat(3, agentInds{:});
 
@@ -24,18 +30,4 @@ function obj = partition(obj)
     [m, n, ~] = size(agentInds);
     [jj, kk] = ndgrid(1:m, 1:n);
     obj.partitioning = agentInds(sub2ind(size(agentInds), jj, kk, idx));
-
-    % Get individual agent sensor performance
-    nowIdx = [0; obj.partitioningTimes] == obj.t;
-    if isnan(obj.t)
-        nowIdx = 1;
-    end
-    for ii = 1:size(obj.agents, 1)
-        idx = obj.partitioning == ii;
-        agentPerformance = squeeze(agentPerformances(:, :, ii));
-        obj.perf(ii, nowIdx) = sum(agentPerformance(idx) .* obj.objective.values(idx));
-    end
-
-    % Current total performance
-    obj.perf(end, nowIdx) = sum(obj.perf(1:(end - 1), nowIdx));
 end

@miSim/plot.m

@@ -6,6 +6,11 @@ function obj = plot(obj)
         obj (1, 1) {mustBeA(obj, 'miSim')};
     end
     
+    % fast exit when plotting is disabled
+    if ~obj.makePlots
+        return;
+    end
+
     % Plot domain
     [obj.domain, obj.f] = obj.domain.plotWireframe(obj.spatialPlotIndices);
 
@@ -17,7 +22,7 @@ function obj = plot(obj)
     % Plot objective gradient
     obj.f = obj.domain.objective.plot(obj.objectivePlotIndices, obj.f);
 
-    % Plot agents and their collision geometries
+    % Plot agents and their collision/communications geometries
     for ii = 1:size(obj.agents, 1)
         [obj.agents{ii}, obj.f] = obj.agents{ii}.plot(obj.spatialPlotIndices, obj.f);
     end
@@ -31,6 +36,9 @@ function obj = plot(obj)
     % Plot domain partitioning
     obj = obj.plotPartitions();
 
+    % Plot agent trails
+    obj = obj.plotTrails();
+
     % Enforce plot limits
     for ii = 1:size(obj.spatialPlotIndices, 2)
         xlim(obj.f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(1), obj.domain.maxCorner(1)]);
@@ -40,4 +48,7 @@ function obj = plot(obj)
 
     % Plot performance
     obj = obj.plotPerformance();
+
+    % Plot h functions
+    obj = obj.plotH();
 end

@miSim/plotConnections.m

@@ -9,9 +9,9 @@ function obj = plotConnections(obj)
     % Iterate over lower triangle off-diagonal region of the 
     % adjacency matrix to plot communications links between agents
     X = []; Y = []; Z = [];
-    for ii = 2:size(obj.adjacency, 1)
+    for ii = 2:size(obj.constraintAdjacencyMatrix, 1)
         for jj = 1:(ii - 1)
-            if obj.adjacency(ii, jj)
+            if obj.constraintAdjacencyMatrix(ii, jj)
                 X = [X; obj.agents{ii}.pos(1), obj.agents{jj}.pos(1)];
                 Y = [Y; obj.agents{ii}.pos(2), obj.agents{jj}.pos(2)];
                 Z = [Z; obj.agents{ii}.pos(3), obj.agents{jj}.pos(3)];

@miSim/plotGraph.m

@@ -7,7 +7,7 @@ function obj = plotGraph(obj)
     end
 
     % Form graph from adjacency matrix
-    G = graph(obj.adjacency, 'omitselfloops');
+    G = graph(obj.constraintAdjacencyMatrix, 'omitselfloops');
 
     % Plot graph object
     if isnan(obj.networkGraphIndex)

@miSim/plotH.m

@@ -0,0 +1,61 @@
+function obj = plotH(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+
+    obj.hf = figure;
+    tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
+
+    nexttile(obj.hf.Children(1));
+    axes(obj.hf.Children(1).Children(1));
+    grid(obj.hf.Children(1).Children(1), "on");
+    xlabel(obj.hf.Children(1).Children(1), "Time (s)"); % ylabel(obj.hf.Children(1).Children(1), "");
+    title(obj.hf.Children(1).Children(1), "Collision Avoidance");
+    hold(obj.hf.Children(1).Children(1), "on");
+    obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)');
+    legendStrings = [];
+    for ii = 2:size(obj.agents, 1)
+        for jj = 1:(ii - 1)
+            legendStrings = [legendStrings; sprintf("A%d A%d", jj, ii)];
+        end
+    end
+    legend(obj.hf.Children(1).Children(1), legendStrings, 'Location', 'bestoutside');
+    hold(obj.hf.Children(1).Children(2), "off");
+
+    nexttile(obj.hf.Children(1));
+    axes(obj.hf.Children(1).Children(1));
+    grid(obj.hf.Children(1).Children(1), "on");
+    xlabel(obj.hf.Children(1).Children(1), "Time (s)"); % ylabel(obj.hf.Children(1).Children(2), "");
+    title(obj.hf.Children(1).Children(1), "Obstacles");
+    hold(obj.hf.Children(1).Children(1), "on");
+    obj.obsPlot = plot(obj.h((1 + (size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)):(((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1)), :)');
+    legendStrings = [];
+    for ii = 1:size(obj.obstacles, 1)
+        for jj = 1:size(obj.agents, 1)
+            legendStrings = [legendStrings; sprintf("A%d O%d", jj, ii)];
+        end
+    end
+    legend(obj.hf.Children(1).Children(1), legendStrings, 'Location', 'bestoutside');
+    hold(obj.hf.Children(1).Children(2), "off");
+
+    nexttile(obj.hf.Children(1));
+    axes(obj.hf.Children(1).Children(1));
+    grid(obj.hf.Children(1).Children(1), "on");
+    xlabel(obj.hf.Children(1).Children(1), "Time (s)"); % ylabel(obj.hf.Children(1).Children(1), "");
+    title(obj.hf.Children(1).Children(1), "Domain");
+    hold(obj.hf.Children(1).Children(1), "on");
+    obj.domPlot = plot(obj.h((1 + (((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1))):size(obj.h, 1), 1:end)');
+    legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], 'Location', 'bestoutside');
+    hold(obj.hf.Children(1).Children(2), "off");
+
+    nexttile(obj.hf.Children(1));
+    axes(obj.hf.Children(1).Children(1));
+    grid(obj.hf.Children(1).Children(1), "on");
+    xlabel(obj.hf.Children(1).Children(1), "Time (s)"); % ylabel(obj.hf.Children(1).Children(1), "");
+    title(obj.hf.Children(1).Children(1), "Communications");
+    % skipped this for now because it is very complicated
+
+end

@miSim/plotPerformance.m

@@ -6,6 +6,13 @@ function obj = plotPerformance(obj)
         obj (1, 1) {mustBeA(obj, 'miSim')};
     end
 
+    % fast exit when plotting is disabled
+    if ~obj.makePlots
+        return;
+    end
+    
+    obj.fPerf = figure;
+
     axes(obj.fPerf);
     title(obj.fPerf.Children(1), "Sensor Performance");
     xlabel(obj.fPerf.Children(1), 'Time (s)');
@@ -15,20 +22,22 @@ function obj = plotPerformance(obj)
     % Plot current cumulative performance
     hold(obj.fPerf.Children(1), 'on');
     o = plot(obj.fPerf.Children(1), obj.perf(end, :));
+    warning('off', 'MATLAB:gui:array:InvalidArrayShape'); % suppress this warning to avoid polluting output
+    o.XData = NaN(1, obj.maxIter); % correct time will be set at runtime
+    o.YData = [0, NaN(1, obj.maxIter - 1)];
     hold(obj.fPerf.Children(1), 'off');
 
     % Plot current agent performance
     for ii = 1:(size(obj.perf, 1) - 1)
         hold(obj.fPerf.Children(1), 'on');
         o = [o; plot(obj.fPerf.Children(1), obj.perf(ii, :))];
+        o(end).XData = NaN(1, obj.maxIter); % correct time will be set at runtime
+        o(end).YData = [0, NaN(1, obj.maxIter - 1)];
         hold(obj.fPerf.Children(1), 'off');
     end
 
     % Add legend
-    agentStrings = repmat("Agent %d", size(obj.perf, 1) - 1, 1);
-    for ii = 1:size(agentStrings, 1)
-        agentStrings(ii) = sprintf(agentStrings(ii), ii);
-    end
+    agentStrings = string(cellfun(@(x) x.label, obj.agents, 'UniformOutput', false));
     agentStrings = ["Total"; agentStrings];
     legend(obj.fPerf.Children(1), agentStrings, 'Location', 'northwest');
 

@miSim/plotTrails.m

@@ -0,0 +1,26 @@
+function obj = plotTrails(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'miSim')}
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'miSim')}
+    end
+    
+    % fast exit when plotting is disabled
+    if ~obj.makePlots
+        return;
+    end
+
+    % Plot full range of position history on each spatial plot axes
+    o = [];
+    for ii = 1:(size(obj.posHist, 1))
+        hold(obj.f.Children(1).Children(obj.spatialPlotIndices(1)), 'on');
+        o = [o; plot3(obj.f.Children(1).Children(obj.spatialPlotIndices(1)), obj.posHist(ii, 1:obj.maxIter, 1), obj.posHist(ii, 1:obj.maxIter, 2), obj.posHist(ii, 1:obj.maxIter, 3), 'Color', 'k', 'LineWidth', 1)];
+        hold(obj.f.Children(1).Children(obj.spatialPlotIndices(1)), 'off');
+    end
+
+    % Copy trails to other figures?
+    obj.trailPlot = o;
+
+    % Add legend?
+end

@miSim/run.m

@@ -7,40 +7,47 @@ function [obj] = run(obj)
     end
 
     % Start video writer
+    if obj.makeVideo
         v = obj.setupVideoWriter();
         v.open();
+    end
     
-    steady = 0;
     for ii = 1:size(obj.times, 1)
         % Display current sim time
         obj.t = obj.times(ii);
+        obj.timestepIndex = ii;
         fprintf("Sim Time: %4.2f (%d/%d)\n", obj.t, ii, obj.maxIter + 1);
 
+        % Validate current simulation configuration
+        obj.validate();
+
         % Check if it's time for new partitions
         updatePartitions = false;
         if ismember(obj.t, obj.partitioningTimes)
-            % Check if it's time to end the sim (performance has settled)
-            if obj.t >= obj.partitioningTimes(5)
-                idx = find(obj.t == obj.partitioningTimes);
-                newMeanTotalPerf = mean(obj.perf(end, ((idx - 5 + 1):idx)));
-                if (obj.oldMeanTotalPerf * 0.95 <= newMeanTotalPerf) && (newMeanTotalPerf <= max(1e-6, obj.oldMeanTotalPerf * 1.05))
-                    steady = steady + 1;
-                    if steady >= 3
-                        fprintf("Performance is stable, terminating early at %4.2f (%d/%d)\n", obj.t, ii, obj.maxIter + 1);
-                        break; % performance is not improving further, exit main sim loop
-                    end
-                end
-                obj.oldMeanTotalPerf = newMeanTotalPerf;
-            end
             updatePartitions = true;
             obj = obj.partition();
         end
 
-        % Iterate over agents to simulate their motion
+        % Determine desired communications links
+        obj = obj.lesserNeighbor();
+
+        % Iterate over agents to simulate their unconstrained motion
         for jj = 1:size(obj.agents, 1)
-            obj.agents{jj} = obj.agents{jj}.run(obj.objective, obj.domain, obj.partitioning);
+            obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.t, jj);
         end
 
+        % Adjust motion determined by unconstrained gradient ascent using
+        % CBF constraints solved by QP
+        obj = constrainMotion(obj);
+
+        % Finished simulation for this timestep, do accounting
+
+        % Update agent position history array
+        obj.posHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false)), size(obj.agents, 1), 1, 3);
+
+        % Update total performance
+        obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(end), obj.agents))];
+
         % Update adjacency matrix
         obj = obj.updateAdjacency();
 
@@ -48,10 +55,14 @@ function [obj] = run(obj)
         obj = obj.updatePlots(updatePartitions);
 
         % Write frame in to video
+        if obj.makeVideo
             I = getframe(obj.f);
             v.writeVideo(I);
         end
+    end
 
+    if obj.makeVideo
         % Close video file
         v.close();
     end
+end

@miSim/updateAdjacency.m

@@ -7,26 +7,29 @@ function obj = updateAdjacency(obj)
     end
 
     % Initialize assuming only self-connections
-    A = logical(eye(size(obj.agents, 1)));
+    A = true(size(obj.agents, 1));
 
     % Check lower triangle off-diagonal connections
     for ii = 2:size(A, 1)
         for jj = 1:(ii - 1)
-            if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) <= min([obj.agents{ii}.comRange, obj.agents{jj}.comRange])
-                % Make sure that obstacles don't obstruct the line
-                % of sight, breaking the connection
-                for kk = 1:size(obj.obstacles, 1)
-                    if ~obj.obstacles{kk}.containsLine(obj.agents{ii}.pos, obj.agents{jj}.pos)
-                        A(ii, jj) = true;
-                    end
-                end
-                % need extra handling for cases with no obstacles
-                if isempty(obj.obstacles)
-                    A(ii, jj) = true;
-                end
+            % Check that agents are not out of range
+            if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) > min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])
+                A(ii, jj) = false; % comm range violation
+                continue;
             end
+
+            % % Check that agents do not have their line of sight obstructed
+            % for kk = 1:size(obj.obstacles, 1)
+            %     if obj.obstacles{kk}.containsLine(obj.agents{jj}.pos, obj.agents{ii}.pos)
+            %         A(ii, jj) = false;
+            %     end
+            % end
         end
     end
 
-    obj.adjacency = A | A';
+    obj.adjacency = A & A';
+
+    if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, 'all')
+        warning("Eliminated network connections that were necessary");
+    end
 end

@miSim/updatePlots.m

@@ -7,13 +7,18 @@ function [obj] = updatePlots(obj, updatePartitions)
         obj (1, 1) {mustBeA(obj, 'miSim')};
     end
 
-    % Update agent positions, collision geometries
+    % Fast exit when plotting is disabled
+    if ~obj.makePlots
+        return;
+    end
+
+    % Update agent positions, collision/communication geometries
     for ii = 1:size(obj.agents, 1)
         obj.agents{ii}.updatePlots();
     end
 
-    % The remaining updates might be possible to do in a clever way
-    % that moves existing lines instead of clearing and 
+    % The remaining updates might should all be possible to do in a clever 
+    % way that moves existing lines instead of clearing and 
     % re-plotting, which is much better for performance boost
 
     % Update agent connections plot
@@ -36,19 +41,34 @@ function [obj] = updatePlots(obj, updatePartitions)
         ylim(obj.f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(2), obj.domain.maxCorner(2)]);
         zlim(obj.f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(3), obj.domain.maxCorner(3)]);
     end
+
+    % Update agent trails
+    for ii = 1:size(obj.agents, 1)
+        obj.trailPlot(ii).XData(obj.timestepIndex) = obj.posHist(ii, obj.timestepIndex, 1);
+        obj.trailPlot(ii).YData(obj.timestepIndex) = obj.posHist(ii, obj.timestepIndex, 2);
+        obj.trailPlot(ii).ZData(obj.timestepIndex) = obj.posHist(ii, obj.timestepIndex, 3);
+    end
+
     drawnow;
     
     % Update performance plot
-    if updatePartitions
-        % find index corresponding to the current time
-        nowIdx = [0; obj.partitioningTimes] == obj.t;
-        nowIdx = find(nowIdx);
-
     % Re-normalize performance plot
-        normalizingFactor = 1/max(obj.perf(end, 1:nowIdx));
-        obj.performancePlot(1).YData(1:nowIdx) = obj.perf(end, 1:nowIdx) * normalizingFactor;
-        for ii = 2:size(obj.performancePlot, 1)
-            obj.performancePlot(ii).YData(1:nowIdx) = obj.perf(ii - 1, 1:nowIdx) * normalizingFactor;
-        end
+    normalizingFactor = 1/max(obj.performance(end));
+    obj.performancePlot(1).YData(1:length(obj.performance)) = obj.performance * normalizingFactor;
+    obj.performancePlot(1).XData(obj.timestepIndex) = obj.t;
+    for ii = 2:(size(obj.agents, 1) + 1)
+        obj.performancePlot(ii).YData(1:length(obj.performance)) = obj.agents{ii - 1}.performance * normalizingFactor;
+        obj.performancePlot(ii).XData(obj.timestepIndex) = obj.t;
+    end
+
+    % Update h function plots
+    for ii = 1:size(obj.caPlot, 1)
+        obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
+    end
+    for ii = 1:size(obj.obsPlot, 1)
+        obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex);
+    end
+    for ii = 1:size(obj.domPlot, 1)
+        obj.domPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1) + size(obj.obsPlot, 1), obj.timestepIndex);
     end
 end

@miSim/validate.m

@@ -0,0 +1,12 @@
+function validate(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'miSim')};
+    end
+    arguments (Output)
+    end
+
+    if max(conncomp(graph(obj.adjacency))) ~= 1
+        warning("Network is not connected");
+    end
+
+end

@sensingObjective/initialize.m

@@ -10,6 +10,8 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
         obj (1,1) {mustBeA(obj, 'sensingObjective')};
     end
 
+    obj.discretizationStep = discretizationStep;
+
     obj.groundAlt = domain.minCorner(3);
     obj.protectedRange = protectedRange;
 
@@ -19,8 +21,8 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
     yMin = min(domain.footprint(:, 2));
     yMax = max(domain.footprint(:, 2));
 
-    xGrid = unique([xMin:discretizationStep:xMax, xMax]);
-    yGrid = unique([yMin:discretizationStep:yMax, yMax]);
+    xGrid = unique([xMin:obj.discretizationStep:xMax, xMax]);
+    yGrid = unique([yMin:obj.discretizationStep:yMax, yMax]);
     
     % Store grid points for plotting later
     [obj.X, obj.Y] = meshgrid(xGrid, yGrid);
@@ -35,6 +37,7 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
     % store ground position
     idx = obj.values == 1;
     obj.groundPos = [obj.X(idx), obj.Y(idx)];
+    obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
 
     assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
 end

geometries/@rectangularPrism/closestToPoint.m

@@ -0,0 +1,19 @@
+function cPos = closestToPoint(obj, pos)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
+        pos (:, 3) double;
+    end
+    arguments (Output)
+        cPos (:, 3) double;
+    end
+    cPos = NaN(1, 3);
+    for ii = 1:3
+        if pos(ii) < obj.minCorner(ii)
+            cPos(ii) = obj.minCorner(ii);
+        elseif pos(ii) > obj.maxCorner(ii)
+            cPos(ii) = obj.maxCorner(ii);
+        else
+            cPos(ii) = pos(ii);
+        end
+    end
+end

geometries/@rectangularPrism/containsLine.m

@@ -10,32 +10,37 @@ function c = containsLine(obj, pos1, pos2)
     
     d = pos2 - pos1;
 
-    % edge case where the line is parallel to the geometry
-    if abs(d) < 1e-12
-        % check if it happens to start or end inside or outside of
-        % the geometry
+    % endpoint contained (trivial case)
     if obj.contains(pos1) || obj.contains(pos2)
         c = true;
-        else
-            c = false;
-        end
         return;
     end
 
-    tmin = -inf;        
-    tmax = inf;
-    
-    % Standard case
+    % parameterize the line segment to check for an intersection
+    tMin = 0;
+    tMax = 1;
     for ii = 1:3
+        % line is parallel to geometry
+        if abs(d(ii)) < 1e-12
+            if pos1(ii) < obj.minCorner(ii) || pos1(ii) > obj.maxCorner(ii)
+                c = false;
+                return;
+            end
+        else
             t1 = (obj.minCorner(ii) - pos1(ii)) / d(ii);
-        t2 = (obj.maxCorner(ii) - pos2(ii)) / d(ii);
-        tmin = max(tmin, min(t1, t2));
-        tmax = min(tmax, max(t1, t2));
-        if tmin > tmax
+            t2 = (obj.maxCorner(ii) - pos1(ii)) / d(ii);
+
+            tLow  = min(t1, t2);
+            tHigh = max(t1, t2);
+
+            tMin = max(tMin, tLow);
+            tMax = min(tMax, tHigh);
+
+            if tMin > tMax
                 c = false;
                 return;
             end
         end
-    
-    c = (tmax >= 0) && (tmin <= 1);
+    end
+    c = true;
 end

geometries/@rectangularPrism/distance.m

@@ -4,7 +4,7 @@ function d = distance(obj, pos)
         pos (:, 3) double;
     end
     arguments (Output)
-        d (:, 1) double
+        d (:, 1) double;
     end
     if obj.contains(pos)
         % Queried point is inside geometry

geometries/@rectangularPrism/distanceGradient.m

@@ -0,0 +1,42 @@
+function g = distanceGradient(obj, pos)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
+        pos (:, 3) double;
+    end
+    arguments (Output)
+        g (:, 3) double
+    end
+    
+    % find nearest point on surface to query position
+    q = min(max(pos, obj.minCorner), obj.maxCorner);
+
+    % Find distance and direction between pos and q
+    v = pos - q;
+    vNorm = norm(v);
+
+    % position is outside geometry
+    if vNorm > 0
+        % gradient is normalized vector from q to p
+        g = v / vNorm;
+        return;
+    end
+
+    % position is on or in geometry
+    % find distances to each face in each dimension
+    distances = [pos(1) - obj.minCorner(1), obj.maxCorner(1) - pos(1), pos(2) - obj.minCorner(2), obj.maxCorner(2) - pos(2), pos(3) - obj.minCorner(3), obj.maxCorner(3) - pos(3)];
+    [~, idx] = min(distances);
+
+    % I think there needs to be additional handling here for the
+    % edge/corner cases, where there are ways to balance or resolve ties
+    % when two faces are equidistant to the query position
+    assert(sum(idx) == idx, "Implement edge case handling");
+
+    % select gradient that brings us quickest to the nearest face
+    g = [ 1,  0,  0; ...
+         -1,  0,  0; ...
+          0,  1,  0; ...
+          0, -1,  0; ...
+          0,  0,  1; ...
+          0,  0, -1;];
+    g = g(idx, :);
+end

geometries/@rectangularPrism/initialize.m

@@ -24,6 +24,10 @@ function obj = initialize(obj, bounds, tag, label, objectiveFunction, discretiza
     % Compute center
     obj.center = obj.minCorner + obj.dimensions ./ 2;
 
+    % Compute a (fake) radius
+    % fully contains the rectangular prism from the center
+    obj.radius = (1/2) * sqrt(sum(obj.dimensions.^2));
+
     % Compute vertices
     obj.vertices = [obj.minCorner;
                     obj.maxCorner(1), obj.minCorner(2:3);
@@ -44,4 +48,13 @@ function obj = initialize(obj, bounds, tag, label, objectiveFunction, discretiza
     if tag == REGION_TYPE.DOMAIN
         obj.objective = sensingObjective;
     end
+
+    % Initialize CBF
+    % first part evaluates to +/-1 if the point is outside/inside the collision geometry
+    % Second part determines the distance from the point to the boundary of the collision geometry
+    obj.barrierFunction = @(x) (1 - 2 * obj.collisionGeometry.contains(x)) * obj.collisionGeometry.distance(x); % x is 1x3
+    % gradient of barrier function 
+    obj.dBarrierFunction = @(x) obj.collisionGeometry.distanceGradient(x); % x is 1x3
+    % as long as the collisionGeometry object is updated during runtime,
+    % these functions never have to be updated again
 end

geometries/@rectangularPrism/initializeRandom.m

@@ -1,4 +1,4 @@
-function [obj] = initializeRandom(obj, tag, label, minDimension, maxDimension, domain)
+function [obj] = initializeRandom(obj, tag, label, minDimension, maxDimension, domain, minAlt)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
         tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
@@ -6,6 +6,7 @@ function [obj] = initializeRandom(obj, tag, label, minDimension, maxDimension, d
         minDimension (1, 1) double = 10;
         maxDimension (1, 1) double = 20;
         domain (1, 1) {mustBeGeometry} = rectangularPrism;
+        minAlt (1, 1) double = 0;
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
@@ -27,7 +28,7 @@ function [obj] = initializeRandom(obj, tag, label, minDimension, maxDimension, d
         while ~domain.contains(candidateMaxCorner) || all(domain.objective.groundPos + domain.objective.protectedRange >= candidateMinCorner(1:2), 2) && all(domain.objective.groundPos - domain.objective.protectedRange <= candidateMaxCorner(1:2), 2)
             if ii == 0 || ii > 10
                 candidateMinCorner = domain.random();
-                candidateMinCorner(3) = 0; % bind to floor
+                candidateMinCorner(3) = minAlt; % bind to floor (plus minimum altitude constraint)
                 ii = 1;
             end
 

geometries/@rectangularPrism/rectangularPrism.m

@@ -3,7 +3,6 @@ classdef rectangularPrism
     properties (SetAccess = private, GetAccess = public)
         % Meta
         tag = REGION_TYPE.INVALID;
-        label = "";
 
         % Spatial
         minCorner = NaN(1, 3);
@@ -11,6 +10,7 @@ classdef rectangularPrism
         dimensions = NaN(1, 3);
         center = NaN;
         footprint = NaN(4, 2);
+        radius = NaN; % fake radius
 
         % Graph
         vertices = NaN(8, 3);
@@ -20,8 +20,13 @@ classdef rectangularPrism
 
         % Plotting
         lines;
+
+        % collision
+        barrierFunction;
+        dBarrierFunction;
     end
     properties (SetAccess = public, GetAccess = public)
+        label = "";
         % Sensing objective (for DOMAIN region type only)
         objective;
     end
@@ -31,7 +36,9 @@ classdef rectangularPrism
         [obj   ] = initializeRandom(obj, tag, label, minDimension, maxDimension, domain);
         [r     ] = random(obj);
         [c     ] = contains(obj, pos);
+        [cPos  ] = closestToPoint(obj, pos);
         [d     ] = distance(obj, pos);
+        [g     ] = distanceGradient(obj, pos);
         [c     ] = containsLine(obj, pos1, pos2);
         [obj, f] = plotWireframe(obj, ind, f);
     end

geometries/@spherical/contains.m

@@ -0,0 +1,10 @@
+function c = contains(obj, pos)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+        pos (:, 3) double;
+    end
+    arguments (Output)
+        c (:, 1) logical
+    end
+    c = norm(obj.center - pos) <= obj.radius;
+end

geometries/@spherical/containsLine.m

@@ -0,0 +1,28 @@
+function c = containsLine(obj, pos1, pos2)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+        pos1 (1, 3) double;
+        pos2 (1, 3) double;
+    end
+    arguments (Output)
+        c (1, 1) logical
+    end
+    
+    d = pos2 - pos1;
+    f = pos1 - obj.center;
+
+    a = dot(d, d);
+    b = 2 * dot(f, d);
+    c = dot(f, f) - obj.radius^2;
+
+    disc = b^2 - 4*a*c;
+
+    if disc < 0
+        c = false;
+        return;
+    end
+
+    t = [(-b - sqrt(disc)) / (2 * a), (-b + sqrt(disc)) / (2 * a)];
+
+    c = (t(1) >= 0 && t(1) <= 1) || (t(2) >= 0 && t(2) <= 1);
+end

geometries/@spherical/initialize.m

@@ -0,0 +1,42 @@
+function obj = initialize(obj, center, radius, tag, label)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+        center (1, 3) double;
+        radius  (1, 1) double;
+        tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
+        label (1, 1) string = "";
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+    end
+
+    obj.tag = tag;
+    obj.label = label;
+
+    % Define geometry
+    obj.center = center;
+    obj.radius = radius;
+    obj.diameter = 2 * obj.radius;
+
+    % Initialize CBF
+    obj.barrierFunction = @(x) NaN;
+    % gradient of barrier function 
+    obj.dBarrierFunction = @(x) NaN;
+
+    % fake vertices in a cross pattern
+    obj.vertices = [obj.center + [obj.radius, 0, 0]; ...
+                    obj.center - [obj.radius, 0, 0]; ...
+                    obj.center + [0, obj.radius, 0]; ...
+                    obj.center - [0, obj.radius, 0]; ...
+                    obj.center + [0, 0, obj.radius]; ...
+                    obj.center - [0, 0, obj.radius]];
+    % fake edges in two perpendicular rings
+    obj.edges = [1, 3; ...
+                 3, 2; ...
+                 2, 4; ...
+                 4, 1; ...
+                 1, 5; ...
+                 5, 2; ...
+                 2, 6; ...
+                 6, 1];
+end

geometries/@spherical/plotWireframe.m

@@ -0,0 +1,43 @@
+function [obj, f] = plotWireframe(obj, ind, f)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+        ind (1, :) double = NaN;
+        f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+        f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
+    end
+
+    % Create axes if they don't already exist
+    f = firstPlotSetup(f);
+
+    % Create plotting inputs
+    [X, Y, Z] = sphere(8);
+    % Scale
+    X = X * obj.radius;
+    Y = Y * obj.radius;
+    Z = Z * obj.radius;
+    % Shift
+    X = X + obj.center(1);
+    Y = Y + obj.center(2);
+    Z = Z + obj.center(3);
+
+    % Plot the boundaries of the geometry into 3D view
+    if isnan(ind)
+        o = plot3(f.CurrentAxes, X, Y, Z, '-', 'Color', obj.tag.color, 'LineWidth', 2);
+    else
+        hold(f.Children(1).Children(ind(1)), "on");
+        o = plot3(f.Children(1).Children(ind(1)), X, Y, Z, '-', 'Color', obj.tag.color, 'LineWidth', 2);
+        hold(f.Children(1).Children(ind(1)), "off");
+    end
+
+    % Copy to other requested tiles
+    if numel(ind) > 1
+        for ii = 2:size(ind, 2)
+            o = [o, copyobj(o(:, 1), f.Children(1).Children(ind(ii)))];
+        end
+    end
+
+    obj.lines = o;
+end

geometries/@spherical/random.m

@@ -0,0 +1,15 @@
+function r = random(obj)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'spherical')};
+    end
+    arguments (Output)
+        r (1, 3) double
+    end
+    y = (rand - 0.5) * 2; % uniform draw on [-1, 1]
+    R = sqrt(1 - y^2);
+    lon = (rand - 0.5) * 2 * pi; % uniform draw on [-pi, pi]
+    s = [R * sin(lon), y, R * cos(lon)]; % random point on surface
+    r = s * rand^(1/3); % scaled to random normalized radius [0, 1]
+
+    r = obj.center + obj.radius * r;
+end

geometries/@spherical/spherical.m

@@ -0,0 +1,37 @@
+classdef spherical
+    % Rectangular prism geometry
+    properties (SetAccess = private, GetAccess = public)
+        % Spatial
+        center = NaN;
+        radius = NaN;
+        diameter = NaN;
+
+        vertices; % fake vertices
+        edges; % fake edges
+
+        % Plotting
+        lines;
+
+        % collision
+        barrierFunction;
+        dBarrierFunction;
+    end
+    properties (SetAccess = public, GetAccess = public)
+        % Meta
+        tag = REGION_TYPE.INVALID;
+        label = "";
+        
+        % Sensing objective (for DOMAIN region type only)
+        objective;
+    end
+
+    methods (Access = public)
+        [obj   ] = initialize(obj, center, radius, tag, label);
+        [r     ] = random(obj);
+        [c     ] = contains(obj, pos);
+        [d     ] = distance(obj, pos);
+        [g     ] = distanceGradient(obj, pos);
+        [c     ] = containsLine(obj, pos1, pos2);
+        [obj, f] = plotWireframe(obj, ind, f);
+    end
+end

geometries/REGION_TYPE.m

@@ -9,6 +9,7 @@ classdef REGION_TYPE
         OBSTACLE (2, [255, 127, 127]); % obstacle region
         COLLISION (3, [255, 255, 128]); % collision avoidance region
         FOV (4, [255, 165, 0]); % field of view region
+        COMMS (5, [0, 255, 0]); % comunications region
     end
     methods
         function obj = REGION_TYPE(id, color)

guidanceModels/gradientAscent.m

@@ -1,26 +0,0 @@
-function nextPos = gradientAscent(sensedValues, sensedPositions, pos, rate)
-    arguments (Input)
-        sensedValues (:, 1) double;
-        sensedPositions (:, 3) double;
-        pos (1, 3) double;
-        rate (1, 1) double = 0.1;
-    end
-    arguments (Output)
-        nextPos(1, 3) double;
-    end
-
-    % As a default, maintain current position
-    if size(sensedValues, 1) == 0 && size(sensedPositions, 1) == 0
-        nextPos = pos;
-        return;
-    end
-    
-    % Select next position by maximum sensed value
-    nextPos = sensedPositions(sensedValues == max(sensedValues), :);
-    nextPos = [nextPos(1, 1:2), pos(3)]; % just in case two get selected, simply pick one
-
-    % rate-limit motion
-    v = nextPos - pos;
-    nextPos = pos + (v / norm(v, 2)) * rate;
-
-end

resources/project/EEtUlUb-dLAdf0KpMVivaUlztwA/XCp_6IVryeT94420M1370QjM5u4d.xml

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

resources/project/EEtUlUb-dLAdf0KpMVivaUlztwA/XCp_6IVryeT94420M1370QjM5u4p.xml

@@ -1,2 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<Info location="1d8d2b42-2863-4985-9cf2-980917971eba" type="Reference"/>

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/OJQQt9oLZ-3u4fU3OVlfDGdcdxcp.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/QXWY7O9zl20hsQdVz8SSSmnWtfcp.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/Zm6-Pu5TuNDu7Nb1xPKdbRS1mBId.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/Zm6-Pu5TuNDu7Nb1xPKdbRS1mBIp.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/rTZ-bC86s4c3irmoSemsIqFlUBUd.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/rTZ-bC86s4c3irmoSemsIqFlUBUp.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/rrrOIkYUdFsPpnaydWK8XER8pkwd.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/rrrOIkYUdFsPpnaydWK8XER8pkwp.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/scbJcgEZnU7v24KBE-JNEEeTzakd.xml

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

resources/project/HVl1IMKCtbARK0HKB9fPxObVDd8/scbJcgEZnU7v24KBE-JNEEeTzakp.xml

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

resources/project/NRbCR7m2f1_2pHz6LyHrTz7eFpc/HVl1IMKCtbARK0HKB9fPxObVDd8p.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/OYUaWUmC6jZNQaYWobzy5I-iESkd.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/OYUaWUmC6jZNQaYWobzy5I-iESkp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/_tVnHInN54-Fys1puCBYQ1j4NwUd.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/_tVnHInN54-Fys1puCBYQ1j4NwUp.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/hyvGevruV7eLIdxFdEJJT6QLP1Yd.xml

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

resources/project/SIL3u_W39LwE7HHYsarfFmr9gVQ/hyvGevruV7eLIdxFdEJJT6QLP1Yp.xml

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

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/NSdjf1q7sJuLYHZ864kCIhygPfId.xml

@@ -1,6 +1,2 @@
 <?xml version="1.0" encoding="UTF-8"?>
-<Info>
-    <Category UUID="FileClassCategory">
-        <Label UUID="design"/>
-    </Category>
-</Info>
+<Info/>

resources/project/qaw0eS1zuuY1ar9TdPn1GMfrjbQ/zfqtoTzQztkirqSAjA2vYKiZn2Mp.xml

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

resources/project/tBBDcBPWdBTCTMSBG9IGJ_TsICk/4TB7e-h1cL8M9VKf-O2iM-tNAksd.xml

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

resources/project/tBBDcBPWdBTCTMSBG9IGJ_TsICk/4TB7e-h1cL8M9VKf-O2iM-tNAksp.xml

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

resources/project/tBBDcBPWdBTCTMSBG9IGJ_TsICk/789El5-CdC-5REJUNa0jxTyTfvod.xml

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

resources/project/tBBDcBPWdBTCTMSBG9IGJ_TsICk/789El5-CdC-5REJUNa0jxTyTfvop.xml

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

resources/project/zfqtoTzQztkirqSAjA2vYKiZn2M/H7wWoItGZZXFLdjsjGa3nymk8U8p.xml

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

sensorModels/@sigmoidSensor/sense.m

@@ -1,21 +0,0 @@
-function [values, positions] = sense(obj, agent, sensingObjective, domain, partitioning)
-    arguments (Input)
-        obj (1, 1) {mustBeA(obj, 'sigmoidSensor')};
-        agent (1, 1) {mustBeA(agent, 'agent')};
-        sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
-        domain (1, 1) {mustBeGeometry};
-        partitioning (:, :) double;
-    end
-    arguments (Output)
-        values (:, 1) double;
-        positions (:, 3) double;
-    end
-
-    % Find positions for this agent's assigned partition in the domain
-    idx = partitioning == agent.index;
-    positions = [sensingObjective.X(idx), sensingObjective.Y(idx), zeros(size(sensingObjective.X(idx)))];
-
-    % Evaluate objective function at every point in this agent's
-    % assigned partiton
-    values = sensingObjective.values(idx);
-end

test/test_miSim.m

@@ -3,6 +3,11 @@ classdef test_miSim < matlab.unittest.TestCase
         % System under test
         testClass = miSim;
 
+        % Debug
+        makeVideo = true; % disable video writing for big performance increase
+        makePlots = true; % disable plotting for big performance increase (also disables video)
+        plotCommsGeometry = false; % disable plotting communications geometries
+
         % Sim
         maxIter = 250;
         timestep = 0.05
@@ -11,6 +16,7 @@ classdef test_miSim < matlab.unittest.TestCase
         % Domain
         domain = rectangularPrism; % domain geometry
         minDimension = 10;
+        minAlt = 1; % minimum allowed agent altitude
 
         % Obstacles
         minNumObstacles = 1; % Minimum number of obstacles to be randomly generated
@@ -25,8 +31,8 @@ classdef test_miSim < matlab.unittest.TestCase
         objective = sensingObjective;
 
         % Agents
-        minAgents = 2; % Minimum number of agents to be randomly generated
-        maxAgents = 4; % Maximum number of agents to be randomly generated
+        minAgents = 4; % Minimum number of agents to be randomly generated
+        maxAgents = 6; % Maximum number of agents to be randomly generated
         sensingLength = 0.05; % length parameter used by sensing function
         agents = cell(0, 1);
         
@@ -84,12 +90,13 @@ classdef test_miSim < matlab.unittest.TestCase
                 while badCandidate
                     % Instantiate a rectangular prism obstacle inside the domain
                     tc.obstacles{ii} = rectangularPrism;
-                    tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, tc.domain);
+                    tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, tc.domain, tc.minAlt);
     
                     % Check if the obstacle collides with an existing obstacle
                     if ~tc.obstacleCollisionCheck(tc.obstacles(1:(ii - 1)), tc.obstacles{ii})
                         badCandidate = false;
                     end
+
                 end
             end
 
@@ -104,11 +111,11 @@ classdef test_miSim < matlab.unittest.TestCase
                     if ii == 1
                         while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
                             candidatePos = tc.domain.random();
-                            candidatePos(3) = 1  + rand * 3; % place agents at decent altitudes for sensing
+                            candidatePos(3) = tc.minAlt  + rand * 3; % place agents at decent altitudes for sensing
                         end
                     else
                         candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.comRange/sqrt(2));
-                        candidatePos(3) = 1  + rand * 3; % place agents at decent altitudes for sensing
+                        candidatePos(3) = tc.minAlt  + rand * 3; % place agents at decent altitudes for sensing
                     end
 
                     % Make sure that the candidate position is within the
@@ -148,14 +155,14 @@ classdef test_miSim < matlab.unittest.TestCase
 
                     % Initialize candidate agent collision geometry
                     candidateGeometry = rectangularPrism;
-                    candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", ii));
+                    candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION);
 
                     % Initialize candidate agent sensor model
                     sensor = sigmoidSensor;
                     sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
 
                     % Initialize candidate agent
-                    newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, tc.comRange, ii, sprintf("Agent %d", ii)); 
+                    newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange); 
 
                     % Make sure candidate agent doesn't collide with
                     % domain
@@ -203,7 +210,7 @@ classdef test_miSim < matlab.unittest.TestCase
             end
 
             % Initialize the simulation
-            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles);
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles, tc.makeVideo);
         end
         function misim_run(tc)
             % randomly create obstacles
@@ -216,7 +223,7 @@ classdef test_miSim < matlab.unittest.TestCase
                 while badCandidate
                     % Instantiate a rectangular prism obstacle inside the domain
                     tc.obstacles{ii} = rectangularPrism;
-                    tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, tc.domain);
+                    tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, tc.domain, tc.minAlt);
     
                     % Check if the obstacle collides with an existing obstacle
                     if ~tc.obstacleCollisionCheck(tc.obstacles(1:(ii - 1)), tc.obstacles{ii})
@@ -236,11 +243,11 @@ classdef test_miSim < matlab.unittest.TestCase
                     if ii == 1
                         while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
                             candidatePos = tc.domain.random();
-                            candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, 0.5 + rand * (tc.alphaDistMax * (1.1)  - 0.5)]); % place agents at decent altitudes for sensing
+                            candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, tc.minAlt + rand * (tc.alphaDistMax * (1.1)  - 0.5)]); % place agents at decent altitudes for sensing
                         end
                     else
                         candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.comRange/sqrt(2));
-                        candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, 0.5 + rand * (tc.alphaDistMax * (1.1)  - 0.5)]); % place agents at decent altitudes for sensing
+                        candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, tc.minAlt + rand * (tc.alphaDistMax * (1.1)  - 0.5)]); % place agents at decent altitudes for sensing
                     end
 
                     % Make sure that the candidate position is within the
@@ -279,15 +286,17 @@ classdef test_miSim < matlab.unittest.TestCase
                     end
 
                     % Initialize candidate agent collision geometry
-                    candidateGeometry = rectangularPrism;
-                    candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", ii));
+                    % candidateGeometry = rectangularPrism;
+                    % candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION);
+                    candidateGeometry = spherical;
+                    candidateGeometry = candidateGeometry.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
 
                     % Initialize candidate agent sensor model
                     sensor = sigmoidSensor;
                     sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
 
                     % Initialize candidate agent
-                    newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, tc.comRange, ii, sprintf("Agent %d", ii));
+                    newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, tc.comRange);
                     
                     % Make sure candidate agent doesn't collide with
                     % domain
@@ -335,7 +344,7 @@ classdef test_miSim < matlab.unittest.TestCase
             end
 
             % Initialize the simulation
-            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles);
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles, tc.makeVideo);
 
             % Run simulation loop
             tc.testClass = tc.testClass.run();
@@ -354,8 +363,8 @@ classdef test_miSim < matlab.unittest.TestCase
             dh = [0,0,-1]; % bias agent altitude from domain center
             geometry1 = rectangularPrism;
             geometry2 = geometry1;
-            geometry1 = geometry1.initialize([tc.domain.center + dh + [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh + [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 1));
-            geometry2 = geometry2.initialize([tc.domain.center + dh - [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 2));
+            geometry1 = geometry1.initialize([tc.domain.center + dh + [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh + [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
+            geometry2 = geometry2.initialize([tc.domain.center + dh - [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
             
             % Initialize agent sensor model
             sensor = sigmoidSensor;
@@ -369,18 +378,23 @@ classdef test_miSim < matlab.unittest.TestCase
 
             % Initialize agents
             tc.agents = {agent; agent};
-            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, @gradientAscent, 3*d, 1, sprintf("Agent %d", 1));
-            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, @gradientAscent, 3*d, 2, sprintf("Agent %d", 2));
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, 3*d);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, 3*d);
 
             % Optional third agent along the +Y axis
             geometry3 = rectangularPrism;
-            geometry3 = geometry3.initialize([tc.domain.center + dh - [0, d, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [0, d, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 3));
+            geometry3 = geometry3.initialize([tc.domain.center + dh - [0, d, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [0, d, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
             tc.agents{3} = agent;
-            tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dh - [0, d, 0], zeros(1, 3), 0, 0, geometry3, sensor, @gradientAscent, 3*d, 3, sprintf("Agent %d", 3));
+            tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dh - [0, d, 0], zeros(1, 3), 0, 0, geometry3, sensor, 3*d);
 
             % Initialize the simulation
-            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
-            close(tc.testClass.fPerf);
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1), false, false);
+        
+            tc.verifyEqual(tc.testClass.partitioning(500, 500:502), [2, 3, 1]); % all three near center
+            tc.verifyLessThan(sum(tc.testClass.partitioning == 1, 'all'), sum(tc.testClass.partitioning == 0, 'all')); % more non-assignments than partition 1 assignments
+            tc.verifyLessThan(sum(tc.testClass.partitioning == 2, 'all'), sum(tc.testClass.partitioning == 1, 'all')); % more partition 1 assignments than partition 2 assignments
+            tc.verifyLessThan(sum(tc.testClass.partitioning == 3, 'all'), sum(tc.testClass.partitioning == 2, 'all')); % more partition 3 assignments than partition 2 assignments
+            tc.verifyEqual(unique(tc.testClass.partitioning), [0; 1; 2; 3;]);
         end
         function test_single_partition(tc)
             % make basic domain
@@ -392,7 +406,7 @@ classdef test_miSim < matlab.unittest.TestCase
         
             % Initialize agent collision geometry
             geometry1 = rectangularPrism;
-            geometry1 = geometry1.initialize([[tc.domain.center(1:2), 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2), 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 1));
+            geometry1 = geometry1.initialize([[tc.domain.center(1:2), 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2), 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
             
             % Initialize agent sensor model
             sensor = sigmoidSensor;
@@ -402,15 +416,324 @@ classdef test_miSim < matlab.unittest.TestCase
             sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 20, 3);
 
             % Plot sensor parameters (optional)
-            f = sensor.plotParameters();
+            % f = sensor.plotParameters();
 
             % Initialize agents
             tc.agents = {agent};
-            tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], zeros(1,3), 0, 0, geometry1, sensor, @gradientAscent, 3, 1, sprintf("Agent %d", 1));
+            tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], zeros(1,3), 0, 0, geometry1, sensor, 3);
 
             % Initialize the simulation
-            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1), false, false);
             close(tc.testClass.fPerf);
+
+            tc.verifyEqual(unique(tc.testClass.partitioning), [0; 1]);
+            tc.verifyLessThan(sum(tc.testClass.partitioning == 1, 'all'), sum(tc.testClass.partitioning == 0, 'all'));
+        end
+        function test_single_partition_basic_GA(tc)
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [2, 8]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            geometry1 = rectangularPrism;
+            geometry1 = geometry1.initialize([[tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            % Homogeneous sensor model parameters
+            % sensor = sensor.initialize(2.5666, 5.0807, NaN, NaN, 20.8614, 13); % 13
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 20, 3);
+
+            % Plot sensor parameters (optional)
+            % f = sensor.plotParameters();
+
+            % Initialize agents
+            tc.agents = {agent};
+            tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/3, 3], zeros(1,3), 0, 0, geometry1, sensor, 3, "", false);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, cell(0, 1), true, false);
+            
+            % Run the simulation
+            tc.testClass = tc.testClass.run();
+            if isgraphics(tc.testClass.agents{1}.debugFig)
+                close(tc.testClass.agents{1}.debugFig);
+            end
+
+            % tc.verifyGreaterThan(tc.testClass.performance(end)/max(tc.testClass.performance), 0.99); % ends up very near a relative maximum
+        end
+        function test_collision_avoidance(tc)
+            % No obstacles
+            % Fixed agent initial conditions
+            % Exaggerated large collision geometries to test CA
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = 1.5;
+            d = [2.5, 0, 0];
+            geometry1 = spherical;
+            geometry2 = spherical;
+            geometry1 = geometry1.initialize(tc.domain.center + d, radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry2.initialize(tc.domain.center - d, radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            % Homogeneous sensor model parameters
+            % sensor = sensor.initialize(2.5666, 5.0807, NaN, NaN, 20.8614, 13); % 13
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+
+            % Initialize agents
+            tc.agents = {agent; agent};
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, zeros(1,3), 0, 0, geometry1, sensor, 5);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, zeros(1,3), 0, 0, geometry2, sensor, 5);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, 50, cell(0, 1), tc.makeVideo, tc.makePlots);
+            
+            % Run the simulation
+            tc.testClass.run();
+        end
+        function test_obstacle_avoidance(tc)
+            % Right now this seems to prove that the communications
+            % constraints are working, but the result is dissatisfying
+
+            % Fixed single obstacle
+            % Fixed two agents initial conditions
+            % Exaggerated large collision geometries
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = 1.1;
+            d = [3, 0, 0];
+
+            yOffset = 0;
+            % choice of 0 leads to the agents getting stuck attempting to go around the obstacle on both sides
+            % choice of 1 leads to one agent easily going around while the other gets stuck and the communications link is broken
+
+            geometry1 = spherical;
+            geometry2 = geometry1;
+            geometry1 = geometry1.initialize(tc.domain.center - d + [0, radius * 1.1 - yOffset, 0], radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry2.initialize(tc.domain.center - d - [0, radius * 1.1 + yOffset, 0], radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+            
+            % Initialize obstacles
+            obstacleLength = 1;
+            tc.obstacles{1} = rectangularPrism;
+            tc.obstacles{1} = tc.obstacles{1}.initialize([tc.domain.center(1:2) - obstacleLength, tc.minAlt; tc.domain.center(1:2) + obstacleLength, tc.domain.maxCorner(3)], REGION_TYPE.OBSTACLE, "Obstacle 1");
+
+            % Initialize agents
+            commsRadius = (2*radius + obstacleLength) * 0.9; % defined such that they cannot go around the obstacle on both sides
+            tc.agents = {agent; agent;};
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, radius * 1.1 - yOffset, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, radius  *1.1 + yOffset, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles, tc.makeVideo);
+            
+            % Run the simulation
+            tc.testClass.run();
+        end
+        function test_communications_constraint(tc)
+            % No obstacles
+            % Fixed two agents initial conditions
+            % Negligible collision geometries
+            % Non-standard domain with two objectives that will try to pull the
+            % agents apart
+            l = 10; % domain size
+            dom = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            dom.objective = dom.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [2, 8]) + mvnpdf([x(:), y(:)], [8, 8]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = 0.1;
+            d = [1, 0, 0];
+            geometry1 = spherical;
+            geometry2 = geometry1;
+            geometry1 = geometry1.initialize(dom.center + d, radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry2.initialize(dom.center - d, radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+            
+            % Initialize obstacles
+            tc.obstacles = {};
+            
+            % Initialize agents
+            commsRadius = 4; % defined such that they cannot reach their objective without breaking connectivity
+            tc.agents = {agent; agent;};
+            tc.agents{1} = tc.agents{1}.initialize(dom.center + d, zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
+            tc.agents{2} = tc.agents{2}.initialize(dom.center - d, zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(dom, dom.objective, tc.agents, tc.minAlt, tc.timestep, tc.partitoningFreq, 75, tc.obstacles, true, false);
+            
+            % Run the simulation
+            tc.testClass = tc.testClass.run();
+        end
+        function test_obstacle_blocks_comms_LOS(tc)
+            % Fixed single obstacle
+            % Fixed two agents initial conditions
+            % Exaggerated large communications radius
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = .25;
+            d = 2;
+            geometry1 = spherical;
+            geometry2 = geometry1;
+            geometry1 = geometry1.initialize(tc.domain.center - [d, 0, 0], radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry2.initialize(tc.domain.center - [0, d, 0], radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+
+            % Initialize agents
+            commsRadius = 5;
+            tc.agents = {agent; agent;};
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
+            
+            % Initialize obstacles
+            obstacleLength = 1.5;
+            tc.obstacles{1} = rectangularPrism;
+            tc.obstacles{1} = tc.obstacles{1}.initialize([tc.domain.center(1:2) - obstacleLength, 0; tc.domain.center(1:2) + obstacleLength, tc.domain.maxCorner(3)], REGION_TYPE.OBSTACLE, "Obstacle 1");
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
+
+            % No communications link should be established
+            tc.assertEqual(tc.testClass.adjacency, logical(eye(2)));
+        end
+        function test_LNA_case_1(tc)
+            % based on example in meeting 
+            % No obstacles
+            % Fixed 5 agents initial conditions
+            % unitary communicaitons radius
+            % negligible collision radius
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = .01;
+            d = 1;
+            geometry5 = spherical;
+            geometry1 = geometry5.initialize(tc.domain.center + [d, 0, 0], radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry5.initialize(tc.domain.center, radius, REGION_TYPE.COLLISION);
+            geometry3 = geometry5.initialize(tc.domain.center + [-d, d, 0], radius, REGION_TYPE.COLLISION);
+            geometry4 = geometry5.initialize(tc.domain.center + [-2*d, d, 0], radius, REGION_TYPE.COLLISION);
+            geometry5 = geometry5.initialize(tc.domain.center + [0, d, 0], radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+
+            % Initialize agents
+            commsRadius = d;
+            tc.agents = {agent; agent; agent; agent; agent;};
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
+            tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius);
+            tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius);
+            tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
+
+            % Constraint adjacency matrix defined by LNA should be as follows
+            tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
+                [ 1, 1, 0, 0, 0; ...
+                  1, 1, 0, 0, 1; ...
+                  0, 0, 1, 1, 1;
+                  0, 0, 1, 1, 0;
+                  0, 1, 1, 0, 1;]));
+        end
+        function test_LNA_case_2(tc)
+            % based on example in paper Asynchronous Local Construction of Bounded-Degree Network Topologies Using Only Neighborhood Information
+            % No obstacles
+            % Fixed 7 agents initial conditions
+            % unitary communicaitons radius
+            % negligible collision radius
+            % make basic domain
+            l = 10; % domain size
+            tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
+
+            % make basic sensing objective
+            tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], [8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange);
+        
+            % Initialize agent collision geometry
+            radius = .01;
+            d = 1;
+            geometry7 = spherical;
+            geometry1 = geometry7.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], radius, REGION_TYPE.COLLISION);
+            geometry2 = geometry7.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], radius, REGION_TYPE.COLLISION);
+            geometry3 = geometry7.initialize(tc.domain.center + [0.9 * d, 0, 0], radius, REGION_TYPE.COLLISION);
+            geometry4 = geometry7.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], radius, REGION_TYPE.COLLISION);
+            geometry5 = geometry7.initialize(tc.domain.center + [0, 0.9 * d, 0], radius, REGION_TYPE.COLLISION);
+            geometry6 = geometry7.initialize(tc.domain.center, radius, REGION_TYPE.COLLISION);
+            geometry7 = geometry7.initialize(tc.domain.center + [d/2, d/2, 0], radius, REGION_TYPE.COLLISION);
+            
+            % Initialize agent sensor model
+            sensor = sigmoidSensor;
+            alphaDist = l/2; % half of domain length/width
+            sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 15, 3);
+
+            % Initialize agents
+            commsRadius = d;
+            tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
+            tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry1, sensor, commsRadius);
+            tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], zeros(1,3), 0, 0, geometry2, sensor, commsRadius);
+            tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], zeros(1,3), 0, 0, geometry3, sensor, commsRadius);
+            tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], zeros(1,3), 0, 0, geometry4, sensor, commsRadius);
+            tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], zeros(1,3), 0, 0, geometry5, sensor, commsRadius);
+            tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, zeros(1,3), 0, 0, geometry6, sensor, commsRadius);
+            tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], zeros(1,3), 0, 0, geometry7, sensor, commsRadius);
+
+            % Initialize the simulation
+            tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, 0, tc.timestep, tc.partitoningFreq, 125, tc.obstacles, false, false);
+
+            % Constraint adjacency matrix defined by LNA should be as follows
+            tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
+                [ 1, 1, 0, 0, 0, 0, 0; ...
+                  1, 1, 0, 0, 1, 0, 0; ...
+                  0, 0, 1, 1, 0, 0, 0;
+                  0, 0, 1, 1, 0, 1, 0;
+                  0, 1, 0, 0, 1, 1, 0;
+                  0, 0, 0, 1, 1, 1, 1;
+                  0, 0, 0, 0, 0, 1, 1; ]));
         end
     end
 

util/validators/arguments/mustBeGeometry.m

@@ -1,5 +1,5 @@
 function mustBeGeometry(geometry)
-    validGeometries = ["rectangularPrism";];
+    validGeometries = ["rectangularPrism"; "spherical"];
     if isa(geometry, 'cell')
         for ii = 1:size(geometry, 1)
             assert(any(arrayfun(@(x) isa(geometry{ii}, x), validGeometries)), "Geometry in index %d is not a valid geometry class", ii);