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0b63cb4874
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+4
-2
@@ -32,7 +32,9 @@ classdef agent
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properties (SetAccess = private, GetAccess = public)
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initialStepSize = NaN;
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initialMaxAngleStepSize = NaN;
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stepDecayRate = NaN;
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angleStepDecayRate = NaN;
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end
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methods (Access = public)
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@@ -48,8 +50,8 @@ classdef agent
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obj.commsGeometry = spherical;
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end
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[obj] = initialize(obj, pos, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
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[obj] = run(obj, domain, partitioning, t, index, agents);
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[partitioning] = partition(obj, agents, objective)
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[obj] = run(obj, domain, partitioning, t, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents);
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[partitioning, agents] = partition(obj, agents, objective)
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[obj, f] = plot(obj, ind, f);
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updatePlots(obj);
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end
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+5
-2
@@ -1,4 +1,4 @@
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function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, label, plotCommsGeometry)
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function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, initialMaxAngleStepSize, label, plotCommsGeometry)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, "agent")};
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pos (1, 3) double;
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@@ -7,6 +7,7 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
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comRange (1, 1) double;
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maxIter (1, 1) double;
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initialStepSize (1, 1) double = 0.2;
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initialMaxAngleStepSize (1, 1) double = 5.0;
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label (1, 1) string = "";
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plotCommsGeometry (1, 1) logical = false;
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end
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@@ -23,7 +24,9 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
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obj.label = label;
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obj.plotCommsGeometry = plotCommsGeometry;
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obj.initialStepSize = initialStepSize;
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obj.initialMaxAngleStepSize = initialMaxAngleStepSize;
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obj.stepDecayRate = obj.initialStepSize / maxIter;
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obj.angleStepDecayRate = obj.initialMaxAngleStepSize / maxIter;
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% Initialize performance vector
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if coder.target('MATLAB')
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@@ -35,5 +38,5 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
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% Initialize FOV cone
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obj.fovGeometry = cone;
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obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.alphaTilt) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label));
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obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:3)], tand(obj.sensorModel.halfAngle()) * obj.pos(3), obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label), obj.sensorModel.tilt, obj.sensorModel.azimuth);
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end
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+16
-1
@@ -1,4 +1,4 @@
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function [partitioning] = partition(obj, agents, objective)
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function [partitioning, agents] = partition(obj, agents, objective)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, "agent")};
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agents (:, 1) {mustBeA(agents, "cell")};
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@@ -6,6 +6,7 @@ function [partitioning] = partition(obj, agents, objective)
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end
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arguments (Output)
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partitioning (:, :) double;
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agents (:, 1) cell;
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end
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nAgents = size(agents, 1);
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@@ -18,8 +19,22 @@ function [partitioning] = partition(obj, agents, objective)
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% minimum threshold that must be exceeded for any assignment.
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agentPerf = zeros(nPoints, nAgents + 1);
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for aa = 1:nAgents
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if isa(agents{aa}.sensorModel, "sigmoidSensor")
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p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
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[objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
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elseif isa(agents{aa}.sensorModel, "rfSensor")
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otherSensorsIdx = [1:(aa - 1), (aa + 1):size(agents, 1)];
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otherSensors = agents(otherSensorsIdx);
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otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherSensors, "UniformOutput", false));
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otherSensors = cellfun(@(x) x.sensorModel, otherSensors, "UniformOutput", false);
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[p, ~, agents{aa}.sensorModel, otherSensors] = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
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[objective.X(:), objective.Y(:), zeros(nPoints, 1)], otherSensorsPos, otherSensors);
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for k = 1:numel(otherSensorsIdx)
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agents{otherSensorsIdx(k)}.sensorModel = otherSensors{k};
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end
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else
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error("?");
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end
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agentPerf(:, aa) = p(:);
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end
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agentPerf(:, nAgents + 1) = objective.sensorPerformanceMinimum;
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+80
-33
@@ -1,14 +1,15 @@
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function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useDoubleIntegrator, dampingCoeff, dt)
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function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, "agent")};
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domain (1, 1) {mustBeGeometry};
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partitioning (:, :) double;
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timestepIndex (1, 1) double;
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index (1, 1) double;
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agents (:, 1) {mustBeA(agents, "cell")};
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useDoubleIntegrator (1, 1) logical = false;
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dampingCoeff (1, 1) double = 2.0;
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dt (1, 1) double = 1.0;
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optimizeSensorPointing (1, 1) logical = false;
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otherAgents (:, 1) cell = cell();
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, "agent")};
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@@ -33,33 +34,62 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
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maskedX = domain.objective.X(partitionMask);
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maskedY = domain.objective.Y(partitionMask);
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% Compute agent performance at the current position and each delta position +/- X, Y, Z
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delta = domain.objective.discretizationStep; % smallest possible step size that gets different results
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deltaApplicator = [0, 0, 0; 1, 0, 0; -1, 0, 0; 0, 1, 0; 0, -1, 0; 0, 0, 1; 0, 0, -1]; % none, +X, -X, +Y, -Y, +Z, -Z
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C_delta = NaN(7, 1); % agent performance at delta steps in each direction
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for ii = 1:7
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if isa(obj.sensorModel, "rfSensor")
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% Extract other agents' sensor models and positions once, outside the delta loop.
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% Mask the full-grid RSS caches (filled by partition()) down to this agent's
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% partition subset so sensorPerformance can reuse them for all perturbations.
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otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherAgents, "UniformOutput", false));
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otherSensors = cellfun(@(x) x.sensorModel, otherAgents, "UniformOutput", false);
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partitionIndices = find(partitionMask);
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for kk = 1:numel(otherSensors)
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if ~isempty(otherSensors{kk}.rssCache)
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otherSensors{kk}.rssCache = otherSensors{kk}.rssCache(partitionIndices);
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end
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end
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% Pre-mask this agent's own full-grid cache to the partition subset.
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% Used for ii==1 (current position, no perturbation) to avoid recomputing.
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baseSensorModel = obj.sensorModel;
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if ~isempty(obj.sensorModel.rssCache)
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baseSensorModel.rssCache = obj.sensorModel.rssCache(partitionIndices);
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end
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end
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if optimizeSensorPointing
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% Stash actual current sensor model tilt/azimuth before messing with it
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% in these following hypotheticals
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tilt = obj.sensorModel.tilt;
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azimuth = obj.sensorModel.azimuth;
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end
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% Compute agent performance at the current position and each delta position +/- X, Y, Z, tilt, azimuth
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deltaPos = domain.objective.discretizationStep; % smallest possible step size that gets different results
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if optimizeSensorPointing
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deltaAngle = atan2d(domain.objective.discretizationStep, obj.pos(3)); % smallest possible angle derived from smallest possible step size and current height
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end
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deltaApplicator = [0, 0, 0, 0, 0; 1, 0, 0, 0, 0; -1, 0, 0, 0, 0; 0, 1, 0, 0, 0; 0, -1, 0, 0, 0; 0, 0, 1, 0, 0; 0, 0, -1, 0, 0; 0, 0, 0, 1, 0; 0, 0, 0, -1, 0; 0, 0, 0, 0, 1; 0, 0, 0, 0, -1;]; % none, +X, -X, +Y, -Y, +Z, -Z, +tilt, -tilt, +azimuth, -azimuth
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C_delta = NaN(size(deltaApplicator, 1), 1); % agent performance at delta steps in each direction
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for ii = 1:size(deltaApplicator, 1)
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if ~optimizeSensorPointing && ii > 7; break; end
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% Apply delta to position
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pos = obj.pos + delta * deltaApplicator(ii, 1:3);
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pos = obj.pos + deltaPos * deltaApplicator(ii, 1:3);
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if optimizeSensorPointing
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% Apply delta to tilt and azimuth
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obj.sensorModel.tilt = tilt + deltaAngle * deltaApplicator(ii, 4);
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obj.sensorModel.azimuth = azimuth + deltaAngle * deltaApplicator(ii, 5);
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end
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% Compute performance values on partition
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if ii < 6
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% Compute sensing performance
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if isa(obj.sensorModel, "sigmoidSensor")
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sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
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% Objective performance does not change for 0, +/- X, +/- Y steps.
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% Those values are computed once before the loop and are only
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% recomputed when +/- Z steps are applied
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elseif isa(obj.sensorModel, "rfSensor")
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if ii == 1
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sensorModelForDelta = baseSensorModel; % reuse partition-step cache; no recompute needed
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else
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% Redo partitioning for Z stepping only
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partitioning = obj.partition(agents, domain.objective);
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% Recompute partiton-derived performance values for objective
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partitionMask = partitioning == index;
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objectiveValues = domain.objective.values(partitionMask); % f(omega) on W_n
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% Recompute partiton-derived performance values for sensing
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maskedX = domain.objective.X(partitionMask);
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maskedY = domain.objective.Y(partitionMask);
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sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
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sensorModelForDelta = obj.sensorModel.clearRssCache;
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end
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[sensorValues, ~, ~, ~] = sensorModelForDelta.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))], otherSensorsPos, otherSensors);
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else
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error("?");
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end
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% Rearrange data into image arrays
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@@ -73,37 +103,54 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, agents, useD
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C_delta(ii) = sum(C(~isnan(C)));
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end
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if optimizeSensorPointing
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% Reset sensor model to actual tilt and azimuth angles
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obj.sensorModel.tilt = tilt;
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obj.sensorModel.azimuth = azimuth;
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end
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% Store agent performance at current time and place
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if coder.target('MATLAB')
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obj.performance(timestepIndex + 1) = C_delta(1);
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end
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% Compute gradient by finite central differences
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gradC = [(C_delta(2)-C_delta(3))/(2*delta), (C_delta(4)-C_delta(5))/(2*delta), (C_delta(6)-C_delta(7))/(2*delta)];
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gradC = [(C_delta(2)-C_delta(3))/(2*deltaPos), (C_delta(4)-C_delta(5))/(2*deltaPos), (C_delta(6)-C_delta(7))/(2*deltaPos)];
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if optimizeSensorPointing
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gradC(4) = (C_delta(8) -C_delta(9)) /(2*deltaAngle);
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gradC(5) = (C_delta(10)-C_delta(11))/(2*deltaAngle);
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end
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% Compute scaling factor
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targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
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gradNorm = norm(gradC);
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targetPosRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
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gradPosNorm = norm(gradC(1:3));
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% Compute unconstrained next state
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if useDoubleIntegrator
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% Double-integrator: gradient produces desired acceleration with damping
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if gradNorm < 1e-100
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a_gradient = zeros(1, 3);
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if gradPosNorm < 1e-100
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a_gradient = zeros(1, 5);
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else
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% Scale so steady-state step ≈ targetRate (matching SI behavior)
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a_gradient = (targetRate * dampingCoeff / (gradNorm * dt)) * gradC;
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a_gradient = (targetPosRate * dampingCoeff / (gradPosNorm * dt)) * gradC;
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end
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% Semi-implicit Euler: unconditionally stable for any dampingCoeff and dt
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obj.vel = (obj.vel + a_gradient * dt) / (1 + dampingCoeff * dt);
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obj.vel = (obj.vel + a_gradient(1:3) * dt) / (1 + dampingCoeff * dt);
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obj.pos = obj.lastPos + obj.vel * dt;
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else
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% Single-integrator: gradient directly sets position step
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if gradNorm >= 1e-100
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obj.pos = obj.pos + (targetRate / gradNorm) * gradC;
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if gradPosNorm >= 1e-100
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obj.pos = obj.pos + (targetPosRate / gradPosNorm) * gradC(1:3);
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end
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end
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% Update tilt and azimuth, saturating at the decaying maximum allowed step size
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if optimizeSensorPointing
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maxAngleStep = obj.initialMaxAngleStepSize - obj.angleStepDecayRate * timestepIndex;
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obj.sensorModel.tilt = obj.sensorModel.tilt + sign(gradC(4)) * min(abs(gradC(4)), maxAngleStep);
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obj.sensorModel.azimuth = obj.sensorModel.azimuth + sign(gradC(5)) * min(abs(gradC(5)), maxAngleStep);
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end
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% Reinitialize collision geometry in the new position
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d = obj.pos - obj.collisionGeometry.center;
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if isa(obj.collisionGeometry, "rectangularPrism")
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+32
-9
@@ -7,11 +7,15 @@ function updatePlots(obj)
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% Find change in agent position since last timestep
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deltaPos = obj.pos - obj.lastPos;
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if all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3))
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% Agent did not move, so nothing has to move on the plots
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posChanged = ~(all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3)));
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orientChanged = obj.sensorModel.tilt ~= obj.fovGeometry.tilt || ...
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obj.sensorModel.azimuth ~= obj.fovGeometry.azimuth;
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if ~posChanged && ~orientChanged
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return;
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end
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if posChanged
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% Scatterplot point positions
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for ii = 1:size(obj.scatterPoints, 1)
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obj.scatterPoints(ii).XData = obj.pos(1);
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@@ -21,7 +25,6 @@ function updatePlots(obj)
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% Collision geometry edges
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for jj = 1:size(obj.collisionGeometry.lines, 2)
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% Update plotting
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for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
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obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
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obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
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@@ -39,13 +42,33 @@ function updatePlots(obj)
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end
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end
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end
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end
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% FOV cone: recompute full mesh whenever position or orientation changes
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if ~isempty(obj.fovGeometry.surface)
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% Sync fovGeometry state to current agent position and sensor orientation
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obj.fovGeometry = obj.fovGeometry.initialize( ...
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obj.pos, obj.fovGeometry.radius, obj.fovGeometry.height, ...
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obj.fovGeometry.tag, obj.fovGeometry.label, ...
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obj.sensorModel.tilt, obj.sensorModel.azimuth);
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% Recompute cone mesh (mirrors cone.plot logic)
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maxAlt = obj.fovGeometry.surface(1).Parent.ZLim(2);
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scalingFactor = maxAlt / obj.fovGeometry.height;
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[X, Y, Z] = cylinder([scalingFactor * obj.fovGeometry.radius, 0], obj.fovGeometry.n);
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Z = Z * maxAlt;
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Ry = [cosd(obj.fovGeometry.tilt), 0, -sind(obj.fovGeometry.tilt); 0, 1, 0; sind(obj.fovGeometry.tilt), 0, cosd(obj.fovGeometry.tilt)];
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Rz = [sind(obj.fovGeometry.azimuth), -cosd(obj.fovGeometry.azimuth), 0; cosd(obj.fovGeometry.azimuth), sind(obj.fovGeometry.azimuth), 0; 0, 0, 1];
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R = Rz * Ry;
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pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
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X = reshape(pts(1, :), size(X)) + obj.pos(1);
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Y = reshape(pts(2, :), size(Y)) + obj.pos(2);
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Z = reshape(pts(3, :) + maxAlt, size(Z)) + obj.pos(3) - maxAlt;
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% Update FOV geometry surfaces
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for jj = 1:size(obj.fovGeometry.surface, 2)
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% Update each plot
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% obj.fovGeometry = obj.fovGeometry.plot(obj.spatialPlotIndices)
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obj.fovGeometry.surface(jj).XData = obj.fovGeometry.surface(jj).XData + deltaPos(1);
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obj.fovGeometry.surface(jj).YData = obj.fovGeometry.surface(jj).YData + deltaPos(2);
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obj.fovGeometry.surface(jj).ZData = obj.fovGeometry.surface(jj).ZData + deltaPos(3);
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obj.fovGeometry.surface(jj).XData = X;
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obj.fovGeometry.surface(jj).YData = Y;
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obj.fovGeometry.surface(jj).ZData = Z;
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||||
end
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||||
end
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||||
end
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||||
@@ -61,7 +61,9 @@ function [obj] = constrainMotion(obj)
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||||
end
|
||||
|
||||
idx = length(h(triu(true(size(h)), 1)));
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
|
||||
end
|
||||
idx = idx + 1;
|
||||
|
||||
hObs = NaN(nAgents, size(obj.obstacles, 1));
|
||||
@@ -84,7 +86,9 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
|
||||
end
|
||||
idx = idx + numel(hObs);
|
||||
|
||||
% Set up domain constraints (walls and ceiling only)
|
||||
@@ -128,13 +132,10 @@ function [obj] = constrainMotion(obj)
|
||||
b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
|
||||
idx = idx + 6;
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
% Save off h function values (logging only — not needed in compiled mode)
|
||||
obj.h(:, obj.timestepIndex) = [h(triu(true(nAgents), 1)); reshape(hObs, [], 1); h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax;];
|
||||
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
|
||||
end
|
||||
idx = idx + 6;
|
||||
end
|
||||
|
||||
% Add communication network constraints
|
||||
@@ -164,7 +165,10 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
|
||||
end
|
||||
|
||||
% Double-integrator: transform QP from velocity to acceleration space.
|
||||
% Single-integrator constraint: A * v <= b
|
||||
|
||||
+3
-3
@@ -1,4 +1,4 @@
|
||||
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology)
|
||||
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology, optimizeSensorPointing)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
domain (1, 1) {mustBeGeometry};
|
||||
@@ -14,6 +14,7 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
useDoubleIntegrator (1, 1) logical = false;
|
||||
dampingCoeff (1, 1) double = 2.0;
|
||||
useFixedTopology (1, 1) logical = false;
|
||||
optimizeSensorPointing (1, 1) logical = false;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
@@ -93,6 +94,7 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
obj.useDoubleIntegrator = useDoubleIntegrator;
|
||||
obj.dampingCoeff = dampingCoeff;
|
||||
obj.useFixedTopology = useFixedTopology;
|
||||
obj.optimizeSensorPointing = optimizeSensorPointing;
|
||||
|
||||
% Compute adjacency matrix and network topology
|
||||
obj = obj.updateAdjacency();
|
||||
@@ -109,8 +111,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
% Prepare performance data store (at t = 0, all have 0 performance)
|
||||
obj.perf = [zeros(size(obj.agents, 1) + 1, 1), NaN(size(obj.agents, 1) + 1, size(obj.partitioningTimes, 1) - 1)];
|
||||
|
||||
% Prepare h function data store
|
||||
obj.h = NaN(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2 + size(obj.agents, 1) * size(obj.obstacles, 1) + 6, size(obj.times, 1));
|
||||
end
|
||||
|
||||
% Create initial partitioning
|
||||
|
||||
@@ -0,0 +1,87 @@
|
||||
function obj = initializeFromInits(obj, initsPath)
|
||||
% INITIALIZEFROMINITS Initialize miSim from a saved simInits matfile.
|
||||
%
|
||||
% Loads all simulation parameters and initial agent states written by
|
||||
% writeInits(), reconstructs domain, objective, agents, and obstacles, then
|
||||
% calls the standard obj.initialize() method. Plots and video are disabled.
|
||||
%
|
||||
% Usage:
|
||||
% sim = sim.initializeFromInits('sandbox/2025_01_01_12_00_00_miSimInits.mat');
|
||||
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
initsPath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
end
|
||||
|
||||
inits = load(initsPath);
|
||||
|
||||
% ---- Build domain ------------------------------------------------------------
|
||||
dom = rectangularPrism;
|
||||
dom = dom.initialize([inits.domainMin; inits.domainMax], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% ---- Build sensing objective -------------------------------------------------
|
||||
dom.objective = sensingObjective;
|
||||
% reshape guards against MATLAB flattening the 1×2×2 singleton dimension on load
|
||||
objSigma = reshape(inits.objectiveSigma, [1 2 2]);
|
||||
objFcn = objectiveFunctionWrapper(inits.objectivePos, objSigma);
|
||||
dom.objective = dom.objective.initialize(objFcn, dom, ...
|
||||
inits.discretizationStep, inits.protectedRange, inits.sensorPerformanceMinimum, ...
|
||||
inits.objectivePos, objSigma);
|
||||
|
||||
% ---- Build agents ------------------------------------------------------------
|
||||
numAgents = inits.numAgents;
|
||||
agentList = cell(numAgents, 1);
|
||||
for ii = 1:numAgents
|
||||
pos = inits.pos(ii, :);
|
||||
|
||||
sensor = sigmoidSensor;
|
||||
sensor = sensor.initialize(inits.alphaDist(ii), inits.betaDist(ii), ...
|
||||
inits.alphaTilt(ii), inits.betaTilt(ii));
|
||||
|
||||
geom = spherical;
|
||||
geom = geom.initialize(pos, inits.collisionRadius(ii), REGION_TYPE.COLLISION, ...
|
||||
sprintf("UAV %d Collision", ii));
|
||||
ag = agent;
|
||||
ag = ag.initialize(pos, geom, sensor, inits.comRange(ii), inits.maxIter, ...
|
||||
inits.initialStepSize(ii), sprintf("UAV %d", ii));
|
||||
agentList{ii} = ag;
|
||||
end
|
||||
|
||||
% ---- Build obstacles ---------------------------------------------------------
|
||||
numObstacles = inits.numObstacles;
|
||||
obstacleList = cell(numObstacles, 1);
|
||||
if numObstacles > 0
|
||||
for ii = 1:numObstacles
|
||||
obs = rectangularPrism;
|
||||
obs = obs.initialize([inits.obsMinCorners(ii, :); inits.obsMaxCorners(ii, :)], ...
|
||||
REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii));
|
||||
obstacleList{ii} = obs;
|
||||
end
|
||||
end
|
||||
|
||||
% ---- Optional backward-compat fields -----------------------------------------
|
||||
if isfield(inits, 'useDoubleIntegrator')
|
||||
useDoubleIntegrator = logical(inits.useDoubleIntegrator);
|
||||
else
|
||||
useDoubleIntegrator = false;
|
||||
end
|
||||
if isfield(inits, 'dampingCoeff')
|
||||
dampingCoeff = inits.dampingCoeff;
|
||||
else
|
||||
dampingCoeff = 2.0;
|
||||
end
|
||||
if isfield(inits, 'useFixedTopology')
|
||||
useFixedTopology = logical(inits.useFixedTopology);
|
||||
else
|
||||
useFixedTopology = false;
|
||||
end
|
||||
|
||||
% ---- Initialize simulation (plots and video disabled) ------------------------
|
||||
obj = obj.initialize(dom, agentList, inits.barrierGain, inits.barrierExponent, ...
|
||||
inits.minAlt, inits.timestep, inits.maxIter, obstacleList, ...
|
||||
false, false, useDoubleIntegrator, dampingCoeff, useFixedTopology);
|
||||
|
||||
end
|
||||
+4
-2
@@ -20,6 +20,7 @@ classdef miSim
|
||||
useDoubleIntegrator = false; % false = single-integrator, true = double-integrator dynamics
|
||||
dampingCoeff = 2.0; % velocity-proportional damping for double-integrator mode
|
||||
useFixedTopology = false; % false = lesser neighbor (dynamic), true = fixed initial topology
|
||||
optimizeSensorPointing = false; % false = fixed sensor tilt/azimuth, true = optimize tilt/azimuth via gradient ascent
|
||||
artifactName = "";
|
||||
f; % main plotting tiled layout figure
|
||||
fPerf; % performance plot figure
|
||||
@@ -54,7 +55,6 @@ classdef miSim
|
||||
partitionGraphIndex = 1;
|
||||
|
||||
% CBF plotting
|
||||
h; % h function values
|
||||
hf; % h function plotting figure
|
||||
caPlot; % objects for collision avoidance h function plot
|
||||
obsPlot; % objects for obstacle h function plot
|
||||
@@ -70,8 +70,10 @@ classdef miSim
|
||||
obj.obstacles = {rectangularPrism};
|
||||
obj.agents = {agent};
|
||||
end
|
||||
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo);
|
||||
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology);
|
||||
[obj] = initializeFromCsv(obj, csvPath);
|
||||
[obj] = initializeFromInits(obj, initsPath);
|
||||
[obj] = plotFromSimHist(obj, initsPath, histPath);
|
||||
[obj] = run(obj);
|
||||
[obj] = lesserNeighbor(obj);
|
||||
[obj] = constrainMotion(obj);
|
||||
|
||||
@@ -0,0 +1,93 @@
|
||||
function obj = plotFromSimHist(obj, initsPath, histPath)
|
||||
% PLOTFROMSIMHIST Reconstruct all three miSim plots from saved matfiles.
|
||||
%
|
||||
% Loads the simInits matfile to rebuild domain/obstacle/objective/agent
|
||||
% geometry, then loads the simHist matfile to restore the full time-history
|
||||
% arrays. Produces the same three figures that a live run would generate:
|
||||
% 1. Sensor performance vs. time (obj.fPerf)
|
||||
% 2. Barrier function values vs. time (obj.hf)
|
||||
% 3. 3-D spatial figure with domain, obstacles, objective, agent trails,
|
||||
% and final-timestep communications topology (obj.f)
|
||||
%
|
||||
% Usage:
|
||||
% sim = miSim;
|
||||
% sim = sim.plotFromSimHist( ...
|
||||
% 'sandbox/2025_01_01_12_00_00_miSimHist.mat', ...
|
||||
% 'sandbox/2025_01_01_12_00_00_miSimInits.mat');
|
||||
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
initsPath (1, 1) string;
|
||||
histPath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
end
|
||||
|
||||
% ---- Reconstruct geometry from inits (plots disabled) --------------------
|
||||
obj = obj.initializeFromInits(initsPath);
|
||||
nAgents = size(obj.agents, 1);
|
||||
|
||||
% ---- Load history data ---------------------------------------------------
|
||||
data = load(histPath);
|
||||
out = data.out;
|
||||
|
||||
nHistTimesteps = size(out.barriers, 2);
|
||||
nPosTimesteps = size(out.agent(1).pos, 1);
|
||||
|
||||
% ---- Populate barrier history --------------------------------------------
|
||||
% out.barriers may be narrower than the pre-allocated obj.barriers if the
|
||||
% run was shorter than maxIter; fill what we have and leave the rest NaN.
|
||||
obj.barriers(:, 1:nHistTimesteps) = out.barriers;
|
||||
|
||||
% ---- Populate position history and advance agents to final positions -----
|
||||
for ii = 1:nAgents
|
||||
agentPos = out.agent(ii).pos; % (nPosTimesteps × 3)
|
||||
nPts = size(agentPos, 1);
|
||||
obj.posHist(ii, 1:nPts, :) = reshape(agentPos, [1, nPts, 3]);
|
||||
obj.agents{ii}.pos = agentPos(end, :); % show final position in spatial plot
|
||||
end
|
||||
|
||||
% ---- Set final constraint topology ---------------------------------------
|
||||
obj.constraintAdjacencyMatrix = out.constraintAdjacency(:, :, end);
|
||||
|
||||
% ---- Recompute partitioning at final agent positions ---------------------
|
||||
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
|
||||
% ---- Enable plotting and produce spatial + barrier figures ---------------
|
||||
obj.makePlots = true;
|
||||
obj = obj.plot();
|
||||
|
||||
% ---- Performance figure (built directly — live machinery is incremental) -
|
||||
nPerfTimesteps = numel(out.perf);
|
||||
times = (0:nPerfTimesteps - 1) * obj.timestep;
|
||||
normFactor = 1 / max(out.perf);
|
||||
|
||||
obj.fPerf = figure;
|
||||
ax = axes(obj.fPerf);
|
||||
hold(ax, "on");
|
||||
title(ax, "Sensor Performance");
|
||||
xlabel(ax, "Time (s)");
|
||||
ylabel(ax, "Sensor Performance");
|
||||
grid(ax, "on");
|
||||
|
||||
legendStrings = strings(nAgents + 1, 1);
|
||||
legendStrings(1) = "Total";
|
||||
plot(ax, times, out.perf * normFactor, "LineWidth", 1.5);
|
||||
for ii = 1:nAgents
|
||||
agentPerf = out.agent(ii).perf;
|
||||
agentTimes = times(1:numel(agentPerf));
|
||||
plot(ax, agentTimes, agentPerf * normFactor);
|
||||
if isfield(out.agent(ii), 'label')
|
||||
legendStrings(ii + 1) = string(out.agent(ii).label);
|
||||
else
|
||||
legendStrings(ii + 1) = sprintf("Agent %d", ii);
|
||||
end
|
||||
end
|
||||
legend(ax, legendStrings, "Location", "northwest");
|
||||
hold(ax, "off");
|
||||
|
||||
% Bring spatial figure to the front
|
||||
figure(obj.f);
|
||||
|
||||
end
|
||||
+13
-4
@@ -6,6 +6,10 @@ function obj = plotH(obj)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
end
|
||||
|
||||
nCA = size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2;
|
||||
nObs = size(obj.agents, 1) * size(obj.obstacles, 1);
|
||||
nDom = size(obj.agents, 1) * 6;
|
||||
|
||||
obj.hf = figure;
|
||||
tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
|
||||
|
||||
@@ -15,7 +19,7 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Collision Avoidance");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)');
|
||||
obj.caPlot = plot(obj.barriers(1:nCA, :)');
|
||||
legendStrings = [];
|
||||
for ii = 2:size(obj.agents, 1)
|
||||
for jj = 1:(ii - 1)
|
||||
@@ -31,7 +35,7 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Obstacles");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.obsPlot = plot(obj.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)), :)');
|
||||
obj.obsPlot = plot(obj.barriers((nCA + 1):(nCA + nObs), :)');
|
||||
legendStrings = [];
|
||||
for ii = 1:size(obj.obstacles, 1)
|
||||
for jj = 1:size(obj.agents, 1)
|
||||
@@ -47,8 +51,13 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Domain");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.domPlot = plot(obj.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");
|
||||
obj.domPlot = plot(obj.barriers((nCA + nObs + 1):(nCA + nObs + nDom), :)');
|
||||
domLabels = ["X Min", "X Max", "Y Min", "Y Max", "Z Min", "Z Max"];
|
||||
legendStrings = strings(nDom, 1);
|
||||
for ii = 1:size(obj.agents, 1)
|
||||
legendStrings((ii - 1) * 6 + (1:6)) = sprintf("A%d ", ii) + domLabels;
|
||||
end
|
||||
legend(obj.hf.Children(1).Children(1), legendStrings, "Location", "bestoutside");
|
||||
hold(obj.hf.Children(1).Children(2), "off");
|
||||
|
||||
nexttile(obj.hf.Children(1));
|
||||
|
||||
+18
-2
@@ -10,7 +10,13 @@ function [obj] = run(obj)
|
||||
% Start video writer
|
||||
if obj.makeVideo
|
||||
v = obj.setupVideoWriter();
|
||||
drawnow;
|
||||
v.open();
|
||||
% Capture reference frame size; used to resize frames that deviate
|
||||
% due to figure reflow during plot updates (e.g. in headless mode).
|
||||
I_ref = getframe(obj.f);
|
||||
v.writeVideo(I_ref);
|
||||
videoFrameSize = [size(I_ref.cdata, 2), size(I_ref.cdata, 1)];
|
||||
end
|
||||
end
|
||||
|
||||
@@ -25,9 +31,16 @@ function [obj] = run(obj)
|
||||
obj.validate();
|
||||
end
|
||||
|
||||
% Clear RF sensor caches
|
||||
if isa(obj.agents{1}.sensorModel, "rfSensor")
|
||||
for ss = 1:size(obj.agents, 1)
|
||||
obj.agents{ss}.sensorModel = obj.agents{ss}.sensorModel.clearRssCache;
|
||||
end
|
||||
end
|
||||
|
||||
% Update partitioning before moving (this one is strictly for
|
||||
% plotting purposes, the real partitioning is done by the agents)
|
||||
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
[obj.partitioning, obj.agents] = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
|
||||
% Determine desired communications links
|
||||
if ~obj.useFixedTopology
|
||||
@@ -42,7 +55,7 @@ function [obj] = run(obj)
|
||||
% Moving
|
||||
% Iterate over agents to simulate their unconstrained motion
|
||||
for jj = 1:size(obj.agents, 1)
|
||||
obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep);
|
||||
obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.useDoubleIntegrator, obj.dampingCoeff, obj.timestep, obj.optimizeSensorPointing, obj.agents([1:(jj - 1), (jj + 1):size(obj.agents, 1)]));
|
||||
end
|
||||
|
||||
% Adjust motion determined by unconstrained gradient ascent using
|
||||
@@ -66,6 +79,9 @@ function [obj] = run(obj)
|
||||
% Write frame in to video
|
||||
if obj.makeVideo
|
||||
I = getframe(obj.f);
|
||||
if size(I.cdata, 2) ~= videoFrameSize(1) || size(I.cdata, 1) ~= videoFrameSize(2)
|
||||
I.cdata = imresize(I.cdata, [videoFrameSize(2), videoFrameSize(1)]);
|
||||
end
|
||||
v.writeVideo(I);
|
||||
end
|
||||
end
|
||||
|
||||
@@ -61,13 +61,15 @@ function [obj] = updatePlots(obj)
|
||||
end
|
||||
|
||||
% Update h function plots
|
||||
for ii = 1:size(obj.caPlot, 1)
|
||||
obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
|
||||
nCA = size(obj.caPlot, 1);
|
||||
nObs = size(obj.obsPlot, 1);
|
||||
for ii = 1:nCA
|
||||
obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
|
||||
end
|
||||
for ii = 1:size(obj.obsPlot, 1)
|
||||
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex);
|
||||
for ii = 1:nObs
|
||||
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, 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);
|
||||
obj.domPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + nObs + ii, obj.timestepIndex);
|
||||
end
|
||||
end
|
||||
+2
-2
@@ -20,8 +20,8 @@ function validate(obj)
|
||||
for kk = 1:size(obj.agents, 1)
|
||||
P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner);
|
||||
d = obj.agents{kk}.pos - P;
|
||||
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2
|
||||
error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
|
||||
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 - 1e-3
|
||||
error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, - dot(d, d) + obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
+45
-7
@@ -5,28 +5,66 @@ function writeInits(obj)
|
||||
arguments (Output)
|
||||
end
|
||||
|
||||
% User-supplied obstacles only: initialize() appends a floor obstacle at
|
||||
% the end when minAlt > 0, so exclude it here to avoid double-counting on
|
||||
% reconstruction (initializeFromInits re-adds the floor via minAlt).
|
||||
numInputObs = size(obj.obstacles, 1) - (obj.minAlt > 0);
|
||||
userObstacles = obj.obstacles(1:numInputObs);
|
||||
|
||||
% Collect agent parameters
|
||||
collisionRadii = cellfun(@(x) x.collisionGeometry.radius, obj.agents);
|
||||
if isprop(obj.agents{1}.sensorModel, "alphaDist")
|
||||
% sigmoidSensor parameters
|
||||
alphaDist = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
|
||||
betaDist = cellfun(@(x) x.sensorModel.betaDist, obj.agents);
|
||||
alphaTilt = cellfun(@(x) x.sensorModel.alphaTilt, obj.agents);
|
||||
betaTilt = cellfun(@(x) x.sensorModel.alphaDist, obj.agents);
|
||||
betaTilt = cellfun(@(x) x.sensorModel.betaTilt, obj.agents);
|
||||
|
||||
% others to zero
|
||||
lossExponent = zeros(size(obj.agents));
|
||||
P_TX = zeros(size(obj.agents));
|
||||
BW = zeros(size(obj.agents));
|
||||
f_c = zeros(size(obj.agents));
|
||||
G_RX_dBi = zeros(size(obj.agents));
|
||||
beamwidthExponent = zeros(size(obj.agents));
|
||||
|
||||
elseif isprop(obj.agents{1}.sensorModel, "P_TX")
|
||||
% rfSensor parameters
|
||||
lossExponent = cellfun(@(x) x.sensorModel.lossExponent, obj.agents);
|
||||
P_TX = cellfun(@(x) x.sensorModel.P_TX, obj.agents);
|
||||
BW = cellfun(@(x) x.sensorModel.BW, obj.agents);
|
||||
f_c = cellfun(@(x) x.sensorModel.f_c, obj.agents);
|
||||
G_RX_dBi = cellfun(@(x) x.sensorModel.G_RX_dBi, obj.agents);
|
||||
beamwidthExponent = cellfun(@(x) x.sensorModel.beamwidthExponent, obj.agents);
|
||||
|
||||
% others to zero
|
||||
alphaDist = zeros(size(obj.agents));
|
||||
betaDist = zeros(size(obj.agents));
|
||||
alphaTilt = zeros(size(obj.agents));
|
||||
betaTilt = zeros(size(obj.agents));
|
||||
end
|
||||
% joint parameters
|
||||
tilt = cellfun(@(x) x.sensorModel.tilt, obj.agents);
|
||||
azimuth = cellfun(@(x) x.sensorModel.azimuth, obj.agents);
|
||||
comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
|
||||
initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
|
||||
pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
|
||||
obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, obj.obstacles, 'UniformOutput', false));
|
||||
obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, obj.obstacles, 'UniformOutput', false));
|
||||
obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, userObstacles, 'UniformOutput', false));
|
||||
obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, userObstacles, 'UniformOutput', false));
|
||||
|
||||
% Combine with simulation parameters
|
||||
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ...
|
||||
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter + 1, "minAlt", obj.minAlt, ...
|
||||
"discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
|
||||
"sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
|
||||
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
|
||||
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", numInputObs, ...
|
||||
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
|
||||
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, ...
|
||||
"alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
|
||||
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
|
||||
"tilt", tilt, "azimuth", azimuth, ... % joint sensor parameters
|
||||
"alphaDist", alphaDist, "betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ... % sigmoid sensor parameters
|
||||
"lossExponent", lossExponent, "P_TX", P_TX, "BW", BW, "f_c", f_c, "G_RX_dBi", G_RX_dBi, "beamwidthExponent", beamwidthExponent, ... % RF sensor parameters
|
||||
... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
|
||||
"pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
|
||||
"domainMin", obj.domain.minCorner, "domainMax", obj.domain.maxCorner, ...
|
||||
"obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
|
||||
"objectiveIntegral", sum(obj.domain.objective.values(:)));
|
||||
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
function value = RSS(obj, d, dx, dy, dz)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
d (:, 1) double;
|
||||
dx (:, 1) double;
|
||||
dy (:, 1) double;
|
||||
dz (:, 1) double;
|
||||
end
|
||||
arguments (Output)
|
||||
value (:, 1) double
|
||||
end
|
||||
% Boresight unit vector: [st*sa, st*ca, -ct]
|
||||
% Target direction unit vector: [dx, dy, dz] / d
|
||||
% cos_theta = dot product of the two, computed without per-point trig.
|
||||
st = sind(obj.tilt);
|
||||
ct = cosd(obj.tilt);
|
||||
sa = sind(obj.azimuth);
|
||||
ca = cosd(obj.azimuth);
|
||||
cos_theta = (st .* (dx .* sa + dy .* ca) - ct .* dz) ./ max(d, eps);
|
||||
cos_theta = max(-1, min(1, cos_theta));
|
||||
theta = acosd(cos_theta);
|
||||
gain = 10 .* obj.beamwidthExponent .* log10((1 + cosd(theta)) ./ 2);
|
||||
value = obj.P_TX_dBm + gain + obj.G_RX_dBi - obj.pathLoss(d);
|
||||
end
|
||||
@@ -0,0 +1,11 @@
|
||||
function obj = clearRssCache(obj)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
end
|
||||
|
||||
obj.rssCache = double.empty(0, 1);
|
||||
|
||||
end
|
||||
@@ -0,0 +1,6 @@
|
||||
function [d, dx, dy, dz] = computePointToPoints(~, agentPos, targetPos)
|
||||
dx = targetPos(:,1) - agentPos(1);
|
||||
dy = targetPos(:,2) - agentPos(2);
|
||||
dz = targetPos(:,3) - agentPos(3);
|
||||
d = sqrt(dx.^2 + dy.^2 + dz.^2);
|
||||
end
|
||||
@@ -0,0 +1,23 @@
|
||||
function value = halfAngle(obj)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
end
|
||||
arguments (Output)
|
||||
value (1, 1) double;
|
||||
end
|
||||
% Sweep angular offset from boresight by evaluating transmitterGain at
|
||||
% (obj.tilt + dtheta, obj.azimuth). The cosine difference identity guarantees
|
||||
% the resulting angular offset from boresight equals dtheta exactly,
|
||||
% independent of the actual pointing direction.
|
||||
dtheta = (0:0.1:179.9)';
|
||||
gain = obj.transmitterGain(obj.tilt + dtheta, obj.azimuth * ones(size(dtheta)));
|
||||
target = gain(1) - 3;
|
||||
idx = find(gain <= target, 1);
|
||||
if isempty(idx) || idx == 1
|
||||
value = dtheta(end);
|
||||
return;
|
||||
end
|
||||
% Linear interpolation between bracketing samples
|
||||
value = dtheta(idx-1) + (target - gain(idx-1)) * ...
|
||||
(dtheta(idx) - dtheta(idx-1)) / (gain(idx) - gain(idx-1));
|
||||
end
|
||||
@@ -0,0 +1,32 @@
|
||||
function obj = initialize(obj, txPower, bandwidth, centerFreq, rxGain_dBi, beamwidthExponent, tilt, azimuth, lossExponent)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")}
|
||||
txPower (1, 1) double;
|
||||
bandwidth (1, 1) double;
|
||||
centerFreq (1, 1) double;
|
||||
rxGain_dBi (1, 1) double;
|
||||
beamwidthExponent (1, 1) double;
|
||||
tilt (1, 1) double = 0;
|
||||
azimuth (1, 1) double = 0;
|
||||
lossExponent (1, 1) double = NaN;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")}
|
||||
end
|
||||
|
||||
%% Provided values
|
||||
obj.P_TX = txPower; % Transmit power (W)
|
||||
obj.BW = bandwidth; % Bandwidth (Hz)
|
||||
obj.f_c = centerFreq; % Center frequency (Hz)
|
||||
obj.G_RX_dBi = rxGain_dBi; % Receiving Antenna Gain (dBi)
|
||||
obj.beamwidthExponent = beamwidthExponent; % Defines how focused the antenna beam is
|
||||
obj.lossExponent = lossExponent;
|
||||
|
||||
% Define initial antenna pointing
|
||||
obj.tilt = tilt;
|
||||
obj.azimuth = azimuth;
|
||||
|
||||
%% Computed values
|
||||
obj.P_TX_dBm = 10*log10(obj.P_TX/1e-3); % Transmit power in dBm
|
||||
obj.N = obj.k_B * obj.T_0 * obj.BW; % Thermal noise
|
||||
end
|
||||
@@ -0,0 +1,13 @@
|
||||
function L_FSPL_dB = pathLoss(obj, d)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
d (:, 1) double; % distance from TX to RX
|
||||
end
|
||||
arguments (Output)
|
||||
L_FSPL_dB (:, 1) double
|
||||
end
|
||||
|
||||
% Free Space Path Loss (dB); d clamped away from zero (log undefined at d=0)
|
||||
L_FSPL_dB = obj.lossExponent * 10 * log10(max(d, eps)) + 20 * log10(obj.f_c) + 20 * log10((4*pi)/obj.c);
|
||||
|
||||
end
|
||||
@@ -0,0 +1,125 @@
|
||||
function f = plot(obj, altitude, otherSensorsPos, otherSensors)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
altitude (1, 1) double;
|
||||
otherSensorsPos (:, 3) double = NaN(0, 3);
|
||||
otherSensors (:, 1) cell = cell(0, 1);
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
|
||||
end
|
||||
|
||||
% Clear local caches so this visualization always uses its own grid
|
||||
obj.rssCache = [];
|
||||
for ii = 1:numel(otherSensors)
|
||||
otherSensors{ii}.rssCache = [];
|
||||
end
|
||||
|
||||
% bias other sensors altitudes appropriately
|
||||
otherSensorsPos = otherSensorsPos + [0, 0, altitude];
|
||||
|
||||
% Create grid on which to evalute SINR, SNR
|
||||
agentPos = [0, 0, altitude];
|
||||
d = 10;
|
||||
if ~isempty(otherSensorsPos)
|
||||
d = max(otherSensorsPos(:, 3) * 0.55);
|
||||
d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
|
||||
end
|
||||
c = 0.1;
|
||||
d = ceil(d / c) * c;
|
||||
distances = -d:c:d;
|
||||
[targetPosX, targetPosY] = meshgrid(distances, distances);
|
||||
|
||||
% Compute SINR, SNR
|
||||
[SINR, ~] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
|
||||
SINR = reshape(SINR, size(targetPosX));
|
||||
|
||||
% normalize in linear scale
|
||||
% SINR = 10.^(SINR/10); SINR = SINR ./ max(SINR(:)); SINR = 10 * log10(SINR);
|
||||
|
||||
% Collect sensor positions and boresight parameters for overlay
|
||||
sensorTilts = [obj.tilt; cellfun(@(s) s.tilt, otherSensors)];
|
||||
sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
|
||||
tailScale = 0.5 * d;
|
||||
|
||||
f = figure;
|
||||
surf(targetPosX, targetPosY, zeros(size(targetPosX)), SINR, "EdgeColor", "none");
|
||||
axis(f.Children(1), "image");
|
||||
colormap(f.Children(1), "hot");
|
||||
title("Ground User SINR and -3 dB antenna gain regions");
|
||||
subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
|
||||
c = colorbar;
|
||||
ylabel(c, "SINR (dB)");
|
||||
xlabel("X (m)");
|
||||
ylabel("Y (m)");
|
||||
hold(f.Children(2), "on");
|
||||
scatter3(0, 0, altitude, 100, 'ko', "LineWidth", 2);
|
||||
scatter3(otherSensorsPos(:, 1), otherSensorsPos(:, 2), otherSensorsPos(:, 3), 100, "bx", "LineWidth", 2);
|
||||
qSelf = quiver3(0, 0, altitude, ...
|
||||
tailScale * sind(obj.tilt) * sind(obj.azimuth), ...
|
||||
tailScale * sind(obj.tilt) * cosd(obj.azimuth), ...
|
||||
-tailScale * cosd(obj.tilt), ...
|
||||
0, 'k', 'LineWidth', 1.5);
|
||||
qSelf.MaxHeadSize = 0.75;
|
||||
if ~isempty(otherSensors)
|
||||
qOthers = quiver3(otherSensorsPos(:,1), otherSensorsPos(:,2), otherSensorsPos(:,3), ...
|
||||
tailScale .* sind(sensorTilts(2:end)) .* sind(sensorAzimuths(2:end)), ...
|
||||
tailScale .* sind(sensorTilts(2:end)) .* cosd(sensorAzimuths(2:end)), ...
|
||||
-tailScale .* cosd(sensorTilts(2:end)), ...
|
||||
0, 'b', 'LineWidth', 1.5);
|
||||
qOthers.MaxHeadSize = 0.75;
|
||||
end
|
||||
% Draw half-angle cones co-boresighted with each quiver arrow
|
||||
N = 48;
|
||||
phi = linspace(0, 2*pi, N);
|
||||
[PHI, S] = meshgrid(phi, [0; 1]); % row 1 = apex (s=0), row 2 = base (s=1)
|
||||
allSensors = [{obj}; otherSensors];
|
||||
allPos = [[0, 0, altitude]; otherSensorsPos];
|
||||
for ii = 1:numel(allSensors)
|
||||
ha = allSensors{ii}.halfAngle();
|
||||
tlt = sensorTilts(ii);
|
||||
az = sensorAzimuths(ii);
|
||||
pos = allPos(ii, :);
|
||||
% Cone length: enough that the axis tip is guaranteed below z=0
|
||||
coneLength = 1.1 * pos(3) / max(cosd(tlt), 0.1);
|
||||
% Nadir cone mesh: apex at origin, base at z = -coneLength
|
||||
cX = S .* coneLength .* tand(ha) .* cos(PHI);
|
||||
cY = S .* coneLength .* tand(ha) .* sin(PHI);
|
||||
cZ = -S .* coneLength;
|
||||
% Rotate nadir → boresight (same convention as quiver arrows)
|
||||
Ry = [cosd(tlt), 0, -sind(tlt); 0, 1, 0; sind(tlt), 0, cosd(tlt)];
|
||||
Rz = [sind(az), -cosd(az), 0; cosd(az), sind(az), 0; 0, 0, 1];
|
||||
R = Rz * Ry;
|
||||
pts = R * [cX(:)'; cY(:)'; cZ(:)'];
|
||||
cX = reshape(pts(1,:), size(cX)) + pos(1);
|
||||
cY = reshape(pts(2,:), size(cY)) + pos(2);
|
||||
cZ = reshape(pts(3,:), size(cZ)) + pos(3);
|
||||
if ii == 1
|
||||
fc = [0, 0, 0];
|
||||
else
|
||||
fc = [0, 0, 1];
|
||||
end
|
||||
surf(cX, cY, cZ, "FaceColor", fc, "FaceAlpha", 0.15, "EdgeColor", "none");
|
||||
|
||||
% Conic section: intersect each cone generator with z=0
|
||||
b_vec = R * [0; 0; -1];
|
||||
u_vec = R * [1; 0; 0];
|
||||
v_vec = R * [0; 1; 0];
|
||||
phi_sec = linspace(0, 2*pi, 720)';
|
||||
dirs = cosd(ha) .* b_vec' + sind(ha) .* (cos(phi_sec) .* u_vec' + sin(phi_sec) .* v_vec');
|
||||
t_sec = -pos(3) ./ dirs(:, 3);
|
||||
t_sec(t_sec <= 0) = NaN;
|
||||
sx = pos(1) + t_sec .* dirs(:, 1);
|
||||
sy = pos(2) + t_sec .* dirs(:, 2);
|
||||
plot3(sx, sy, zeros(size(sx)), "Color", fc, "LineWidth", 2);
|
||||
end
|
||||
clim(f.Children(2), [min(SINR(:)), max(SINR(:))]);
|
||||
xlim(f.Children(2), [-d, d]);
|
||||
ylim(f.Children(2), [-d, d]);
|
||||
hold(f.Children(2), "off");
|
||||
zlim([0, Inf]);
|
||||
|
||||
|
||||
|
||||
|
||||
end
|
||||
@@ -0,0 +1,52 @@
|
||||
function f = plotParameters(obj)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
|
||||
end
|
||||
|
||||
% Agent altitude layers and angle sample points
|
||||
alt_values = 10.^[1, 2, 3, 4];
|
||||
t_values = 0:2.5:87.5; % 0=nadir (center), <90=near horizon (edge)
|
||||
a_values = 0:2.5:360;
|
||||
|
||||
[T, A] = meshgrid(t_values, a_values); % Naz x Nel
|
||||
Ar = deg2rad(A);
|
||||
|
||||
f = figure;
|
||||
hold("on");
|
||||
|
||||
for ii = 1:numel(alt_values)
|
||||
alt = alt_values(ii);
|
||||
|
||||
% For agent at altitude alt, ground target at tilt T has slant distance:
|
||||
D = alt ./ cosd(T);
|
||||
|
||||
% Compute RSS for each (d, t, a) triple
|
||||
rss = obj.RSS(D(:), T(:), A(:));
|
||||
Fslice = reshape(rss, size(D));
|
||||
|
||||
% Disc geometry: t=0 (nadir) -> center, t~90 (horizon) -> edge
|
||||
r = log10(alt) .* T ./ 90;
|
||||
X = r .* cos(Ar);
|
||||
Y = r .* sin(Ar);
|
||||
Z = log10(alt) * ones(size(X));
|
||||
|
||||
hs = surf(X, Y, Z, Fslice);
|
||||
hs.EdgeColor = 'none';
|
||||
hs.FaceColor = 'interp';
|
||||
hs.FaceAlpha = 0.25;
|
||||
end
|
||||
|
||||
colormap(turbo);
|
||||
c = colorbar; c.Label.String = "Received Signal Strength (dB)";
|
||||
daspect([1 1 0.2]);
|
||||
xlabel('X (log_{10} units)'); ylabel('Y (log_{10} units)'); zlabel('log_{10} Altitude (m)');
|
||||
set(gca, 'ZDir', 'reverse');
|
||||
view(3);
|
||||
axis("vis3d");
|
||||
grid("on");
|
||||
scatter3(0, 0, 0, 'rx');
|
||||
hold("off");
|
||||
end
|
||||
@@ -0,0 +1,91 @@
|
||||
function f = plotPerformance(obj, altitude, otherSensorsPos, otherSensors)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
altitude (1, 1) double;
|
||||
otherSensorsPos (:, 3) double = NaN(0, 3);
|
||||
otherSensors (:, 1) cell = cell(0, 1);
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) {mustBeA(f, "matlab.ui.Figure")};
|
||||
end
|
||||
|
||||
% Clear local caches so this visualization always uses its own grid
|
||||
obj.rssCache = [];
|
||||
for ii = 1:numel(otherSensors)
|
||||
otherSensors{ii}.rssCache = [];
|
||||
end
|
||||
|
||||
% bias other sensors altitudes appropriately
|
||||
otherSensorsPos = otherSensorsPos + [0, 0, altitude];
|
||||
|
||||
% Create grid on which to evalute SINR, SNR
|
||||
agentPos = [0, 0, altitude];
|
||||
d = 10;
|
||||
if ~isempty(otherSensorsPos)
|
||||
d = max(d, max(vecnorm(otherSensorsPos(:, 1:2), 2, 2)) * 1.25);
|
||||
end
|
||||
c = 0.1;
|
||||
d = ceil(d / c) * c;
|
||||
distances = -d:c:d;
|
||||
[targetPosX, targetPosY] = meshgrid(distances, distances);
|
||||
|
||||
% Compute SINR, SNR
|
||||
[SINR, SNR] = obj.sensorPerformance(agentPos, [targetPosX(:), targetPosY(:), zeros(size(targetPosX(:)))], otherSensorsPos, otherSensors);
|
||||
SINR = reshape(SINR, size(targetPosX));
|
||||
SNR = reshape(SNR, size(targetPosX));
|
||||
|
||||
% normalize in linear scale
|
||||
SINR = 10.^(SINR/10); SINR = SINR ./ max(SINR(:)); SINR = 10 * log10(SINR);
|
||||
SNR = 10.^(SNR/10); SNR = SNR ./ max(SNR(:)); SNR = 10 * log10(SNR);
|
||||
|
||||
% Collect sensor positions and boresight parameters for overlay
|
||||
sensorXY = [0, 0; otherSensorsPos(:, 1:2)];
|
||||
sensorTilts = [obj.tilt; cellfun(@(s) s.tilt, otherSensors)];
|
||||
sensorAzimuths = [obj.azimuth; cellfun(@(s) s.azimuth, otherSensors)];
|
||||
tailScale = 0.5 * d;
|
||||
|
||||
f = figure;
|
||||
tiledlayout(1, 2, TileSpacing="compact", Padding="compact");
|
||||
|
||||
nexttile;
|
||||
imagesc(distances, distances, SNR);
|
||||
axis("image"); set(gca, 'YDir', 'normal');
|
||||
colorbar; xlabel("X (m)"); ylabel("Y (m)");
|
||||
title("Linearly Normalized SNR (dB)");
|
||||
subtitle("No interfering sources");
|
||||
addSensorOverlay(gca, sensorXY(1, 1:2), sensorTilts(1, 1), sensorAzimuths(1, 1), tailScale);
|
||||
|
||||
nexttile;
|
||||
imagesc(distances, distances, SINR);
|
||||
axis("image"); set(gca, 'YDir', 'normal');
|
||||
colorbar; xlabel("X (m)"); ylabel("Y (m)");
|
||||
title("Linearly Normalized SINR (dB)");
|
||||
subtitle(sprintf("%d interfering source(s)", size(otherSensorsPos, 1)));
|
||||
addSensorOverlay(gca, sensorXY, sensorTilts, sensorAzimuths, tailScale);
|
||||
end
|
||||
|
||||
function addSensorOverlay(ax, sensorXY, tilts, azimuths, tailScale)
|
||||
% Draw a marker + boresight arrow for each sensor.
|
||||
% Tail direction follows azimuth convention (0=+Y, 90=+X, clockwise).
|
||||
% Tail length = tailScale * sind(tilt), so nadir (0°) has no tail and
|
||||
% horizon (90°) has the full tailScale length.
|
||||
hold(ax, 'on');
|
||||
for ii = 1:size(sensorXY, 1)
|
||||
x = sensorXY(ii, 1);
|
||||
y = sensorXY(ii, 2);
|
||||
if ii == 1
|
||||
c = [0, 0, 0];
|
||||
mk = 'o';
|
||||
else
|
||||
c = [0.9, 0.2, 0.2];
|
||||
mk = 'x';
|
||||
end
|
||||
scatter(ax, x, y, 80, c, mk, LineWidth=2);
|
||||
if tilts(ii) > 0
|
||||
u = tailScale * sind(tilts(ii)) * sind(azimuths(ii));
|
||||
v = tailScale * sind(tilts(ii)) * cosd(azimuths(ii));
|
||||
quiver(ax, x, y, u, v, 0, Color=c, LineWidth=2, MaxHeadSize=1.0);
|
||||
end
|
||||
end
|
||||
hold(ax, 'off');
|
||||
end
|
||||
@@ -0,0 +1,40 @@
|
||||
classdef rfSensor
|
||||
properties (SetAccess = private, GetAccess = public)
|
||||
% Physical parameters
|
||||
c = 3e8; % Speed of light (m/s)
|
||||
k_B = 1.38e-23 % Boltzmann constant (W/Hz/K) for thermal noise model
|
||||
T_0 = 300; % Ambient temperature (Kelvin) for thermal noise model
|
||||
lossExponent = NaN; % Path loss exponent (2 for free space, up to 6 for the lossiest environments)
|
||||
% Sensor parameters
|
||||
P_TX = NaN; % Transmit power (Watts)
|
||||
BW = NaN; % Bandwidth (Hz)
|
||||
f_c = NaN; % Center frequency (Hz)
|
||||
G_RX_dBi = NaN; % Receiver antenna gain
|
||||
beamwidthExponent = NaN; % Antenna beamwidth exponent for cosine radiation pattern, larger exponent -> narrower beam
|
||||
% Values computed at initialization
|
||||
P_TX_dBm = NaN; % Transmit power (dBm)
|
||||
N = NaN; % Thermal noise
|
||||
% Cached state (per timestep)
|
||||
end
|
||||
properties (Access = public)
|
||||
tilt = NaN; % Antenna boresight tilt (deg): 0=nadir, 90=horizon
|
||||
azimuth = NaN; % Antenna boresight azimuth (deg): 0=+y, 90=+x, 180=-y, 270=-x
|
||||
rssCache (:,1) double = double.empty(0,1); % linear-scale RSS to last ground targets grid
|
||||
end
|
||||
|
||||
methods (Access = public)
|
||||
[obj] = initialize(obj, txPower, bandwidth, centerFreq, rxGain, beamwidthExponent, tilt, azimuth); % initialize sensor, define parameters
|
||||
[SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors); % determine sensor performance for a given single sensor and target geometry
|
||||
[d, dx, dy, dz] = computePointToPoints(obj, agentPos, targetPos);
|
||||
[value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
|
||||
[f] = plotParameters(obj); % debug, plot sensor response as a function of distance and tilt angle
|
||||
[f] = plotPerformance(obj, altitude, otherSensorsPos, otherSensors); % debug, plot SNR or SINR ground heatmap for a given geometry
|
||||
[f] = plot(obj, altitude, otherSensorsPos, otherSensors);
|
||||
obj = clearRssCache(obj);
|
||||
end
|
||||
methods (Access = private)
|
||||
x = RSS(obj, d, dx, dy, dz); % Received signal strength (function of distance and tilt angle)
|
||||
G_TX_dB = transmitterGain(obj, t, a); % Antenna gain for a given TX/RX pair
|
||||
L_FSPL_dB = pathLoss(obj, d); % Free space path loss for a given TX/RX pair
|
||||
end
|
||||
end
|
||||
@@ -0,0 +1,34 @@
|
||||
function [SINR, SNR, obj, otherSensors] = sensorPerformance(obj, agentPos, targetPos, otherSensorsPos, otherSensors)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
agentPos (1, 3) double;
|
||||
targetPos (:, 3) double;
|
||||
otherSensorsPos (:, 3) double = [];
|
||||
otherSensors (:, 1) cell = {};
|
||||
end
|
||||
arguments (Output)
|
||||
SINR (:, 1) double;
|
||||
SNR (:, 1) double;
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
otherSensors (:, 1) cell;
|
||||
end
|
||||
assert(size(otherSensorsPos, 1) == size(otherSensors, 1), "Mismatch in number of other sensor positions (%d) and number of other sensors (%d) provided", size(otherSensorsPos, 1), size(otherSensors, 1));
|
||||
|
||||
if isempty(obj.rssCache)
|
||||
[d, dx, dy, dz] = obj.computePointToPoints(agentPos, targetPos);
|
||||
obj.rssCache = 1e-3 .* 10 .^ (0.1 .* obj.RSS(d, dx, dy, dz)); % dBm → W
|
||||
end
|
||||
S = obj.rssCache;
|
||||
|
||||
I = zeros(size(S));
|
||||
for ii = 1:size(otherSensors, 1)
|
||||
if isempty(otherSensors{ii}.rssCache)
|
||||
[d_o, dx_o, dy_o, dz_o] = otherSensors{ii}.computePointToPoints(otherSensorsPos(ii, 1:3), targetPos);
|
||||
otherSensors{ii}.rssCache = 1e-3 .* 10 .^ (0.1 .* otherSensors{ii}.RSS(d_o, dx_o, dy_o, dz_o)); % dBm → W
|
||||
end
|
||||
I = I + otherSensors{ii}.rssCache;
|
||||
end
|
||||
|
||||
SINR = 10*log10(S ./ (I + obj.N));
|
||||
SNR = 10*log10(S ./ obj.N);
|
||||
end
|
||||
@@ -0,0 +1,23 @@
|
||||
function value = transmitterGain(obj, t, a)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "rfSensor")};
|
||||
t (:, 1) double; % LOS tilt angle
|
||||
a (:, 1) double; % LOS azimuth angle
|
||||
end
|
||||
arguments (Output)
|
||||
value (:, 1) double
|
||||
end
|
||||
if ~isequal(size(t), size(a))
|
||||
error("t and a must be the same size");
|
||||
end
|
||||
|
||||
% Angular offset from boresight via spherical law of cosines
|
||||
% Convention: t=0° nadir, t=90° horizon; a=0° +y, a=90° +x
|
||||
cos_theta = sind(obj.tilt) .* sind(t) .* cosd(a - obj.azimuth) + ...
|
||||
cosd(obj.tilt) .* cosd(t);
|
||||
cos_theta = max(-1, min(1, cos_theta)); % clamp for numerical safety
|
||||
theta = acosd(cos_theta);
|
||||
|
||||
% Cardioid family: peak at boresight (theta=0), null opposite (theta=180°)
|
||||
value = 10 .* obj.beamwidthExponent .* log10((1 + cosd(theta)) ./ 2);
|
||||
end
|
||||
@@ -16,11 +16,11 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
|
||||
end
|
||||
|
||||
% Set random distribution parameters
|
||||
sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
|
||||
sig = reshape([2 + rand * 2, 1; 1, 2 + rand * 2], [1 2 2]);
|
||||
|
||||
% Set up random bivariate normal distribution function
|
||||
objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig);
|
||||
|
||||
% Regular initialization
|
||||
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange);
|
||||
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange, 1e-6, mu(1:2), sig);
|
||||
end
|
||||
@@ -11,19 +11,26 @@ function f = plot(obj, ind, f)
|
||||
% Create axes if they don't already exist
|
||||
f = firstPlotSetup(f);
|
||||
|
||||
normalized = obj.values ./ sum(obj.values, "all");
|
||||
cRange = [min(normalized, [], "all"), max(normalized, [], "all")];
|
||||
|
||||
% Plot gradient on the "floor" of the domain
|
||||
if isnan(ind)
|
||||
hold(f.CurrentAxes, "on");
|
||||
o = surf(f.CurrentAxes, obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
|
||||
ax = f.CurrentAxes;
|
||||
hold(ax, "on");
|
||||
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
|
||||
o.HitTest = "off";
|
||||
o.PickableParts = "none";
|
||||
hold(f.CurrentAxes, "off");
|
||||
clim(ax, cRange);
|
||||
hold(ax, "off");
|
||||
else
|
||||
hold(f.Children(1).Children(ind(1)), "on");
|
||||
o = surf(f.Children(1).Children(ind(1)), obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
|
||||
ax = f.Children(1).Children(ind(1));
|
||||
hold(ax, "on");
|
||||
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
|
||||
o.HitTest = "off";
|
||||
o.PickableParts = "none";
|
||||
hold(f.Children(1).Children(ind(1)), "off");
|
||||
clim(ax, cRange);
|
||||
hold(ax, "off");
|
||||
end
|
||||
|
||||
% Add to other perspectives
|
||||
|
||||
@@ -0,0 +1,9 @@
|
||||
function value = halfAngle(obj)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "sigmoidSensor")};
|
||||
end
|
||||
arguments (Output)
|
||||
value (1, 1) double;
|
||||
end
|
||||
value = obj.alphaTilt;
|
||||
end
|
||||
@@ -1,17 +1,24 @@
|
||||
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt)
|
||||
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
|
||||
alphaDist (1, 1) double;
|
||||
betaDist (1, 1) double;
|
||||
alphaTilt (1, 1) double;
|
||||
betaTilt (1, 1) double;
|
||||
tilt (1, 1) double = 0;
|
||||
azimuth (1, 1) double = 0;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "sigmoidSensor")}
|
||||
end
|
||||
|
||||
% Sensor performance parameters
|
||||
obj.alphaDist = alphaDist;
|
||||
obj.betaDist = betaDist;
|
||||
obj.alphaTilt = alphaTilt;
|
||||
obj.betaTilt = betaTilt;
|
||||
|
||||
% Sensor pointing parameters
|
||||
obj.tilt = tilt;
|
||||
obj.azimuth = azimuth;
|
||||
end
|
||||
@@ -8,16 +8,20 @@ function value = sensorPerformance(obj, agentPos, targetPos)
|
||||
value (:, 1) double;
|
||||
end
|
||||
|
||||
% compute direct distance and distance projected onto the ground
|
||||
d = vecnorm(agentPos - targetPos, 2, 2); % distance from sensor to target
|
||||
x = vecnorm(agentPos(1:2) - targetPos(:, 1:2), 2, 2); % distance from sensor nadir to target nadir (i.e. distance ignoring height difference)
|
||||
% Unit vectors from agent to each target
|
||||
diffs = targetPos - agentPos;
|
||||
d = vecnorm(diffs, 2, 2);
|
||||
dirs = diffs ./ d;
|
||||
|
||||
% compute tilt angle
|
||||
tiltAngle = (180 - atan2d(x, targetPos(:, 3) - agentPos(3))); % degrees
|
||||
% Boresight unit vector: tilt=0 → nadir [0,0,-1]; azimuth 0=+Y, 90=+X clockwise
|
||||
boresight = [sind(obj.tilt)*sind(obj.azimuth), sind(obj.tilt)*cosd(obj.azimuth), -cosd(obj.tilt)];
|
||||
|
||||
% Angular offset from boresight to each target direction
|
||||
angularOffset = acosd(dirs * boresight');
|
||||
|
||||
% Membership functions
|
||||
mu_d = obj.distanceMembership(d);
|
||||
mu_t = obj.tiltMembership(tiltAngle);
|
||||
mu_t = obj.tiltMembership(angularOffset);
|
||||
|
||||
value = mu_d .* mu_t; % assume pan membership is always 1
|
||||
end
|
||||
@@ -6,14 +6,20 @@ classdef sigmoidSensor
|
||||
alphaTilt = NaN; % degrees
|
||||
betaTilt = NaN;
|
||||
end
|
||||
properties (Access = public)
|
||||
% pointing states
|
||||
tilt = 0;
|
||||
azimuth = 0;
|
||||
end
|
||||
|
||||
methods (Access = public)
|
||||
[obj] = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt);
|
||||
[value] = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos);
|
||||
[f] = plotParameters(obj);
|
||||
[obj] = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth); % initialize sensor, define parameters
|
||||
[value] = sensorPerformance(obj, agentPos, targetPos); % determine sensor performance for a given single sensor and target geometry
|
||||
[value] = halfAngle(obj); % tilt angle (deg) at which sensor performance is halved
|
||||
[f] = plotParameters(obj); % debug, plot sensor response as a function of distance and tilt angle
|
||||
end
|
||||
methods (Access = private)
|
||||
x = distanceMembership(obj, d);
|
||||
x = tiltMembership(obj, t);
|
||||
x = distanceMembership(obj, d); % used in computing distance factor of sensor performance
|
||||
x = tiltMembership(obj, t); % used in computing tilt factor of sensor performance
|
||||
end
|
||||
end
|
||||
@@ -164,7 +164,7 @@ class UAVRunner(BasicRunner):
|
||||
|
||||
# Retry connection up to 10 times (~30 seconds total)
|
||||
reader, writer = None, None
|
||||
for attempt in range(10):
|
||||
for attempt in range(100):
|
||||
try:
|
||||
reader, writer = await asyncio.wait_for(
|
||||
asyncio.open_connection(self.server_ip, self.server_port),
|
||||
|
||||
@@ -28,11 +28,11 @@ environments:
|
||||
port: 5000
|
||||
|
||||
testbed:
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
|
||||
mavlink:
|
||||
ip: "192.168.32.26"
|
||||
port: 14550
|
||||
# Controller runs on host machine (192.168.109.1 from E-VM perspective)
|
||||
# Controller runs on host machine (192.168.X.1, generally)
|
||||
controller:
|
||||
ip: "192.168.109.1"
|
||||
ip: "192.168.112.1"
|
||||
port: 5000
|
||||
|
||||
@@ -28,11 +28,11 @@ environments:
|
||||
port: 5000
|
||||
|
||||
testbed:
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
|
||||
mavlink:
|
||||
ip: "192.168.32.26"
|
||||
port: 14550
|
||||
# Controller runs on host machine (192.168.109.1 from E-VM perspective)
|
||||
# Controller runs on host machine (192.168.X.1, generally)
|
||||
controller:
|
||||
ip: "192.168.109.1"
|
||||
ip: "192.168.112.1"
|
||||
port: 5000
|
||||
@@ -1,2 +1,2 @@
|
||||
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
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||||
1, 150, 30.0, 0.1, 2.0, 1, 1, 1, "5.0, 5.0", "25.0, 25.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "80.0, 80.0, 80.0", "55.0, 55.0", "40, 25, 25, 40", 0.15, "15.0, 10.0, 40.0, 5.0, 10.0, 45.0", 1, "1.0, 25.0, 0.0", "30.0, 30.0, 50.0", 1, 2.0, 1
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1, 100, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 80.0", "0.25, 0.25", "8.0, 8.0", "0.1, 0.1", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "66.6, 66.6", "55, 35, 35, 55", 0.15, "15.0, 15.0, 50.0, 40.0, 15.0, 50.0", 1, "0.0, 35.0, 0.0", "50, 40.0, 60", 1, 2.0, 1
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|
@@ -0,0 +1,2 @@
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timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
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||||
1, 50, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "60.0, 80.0, 45.0, 70.0", "70, 15, 15, 20, 20, 15, 15, 70", 0.15, "10.0, 10.0, 50.0, 40.0, 15.0, 45.0", 8, "0.0, 30.0, 0.0, 42.0, 30.0, 0.0, 84.0, 30.0, 0.0, 13.0, 60.0, 0.0, 55.0, 60.0, 0.0, 0.0, 90, 0.0, 42.0, 90.0, 0.0, 84.0, 90.0, 0.0", "16.0, 40.0, 100.0, 58.0, 40.0, 100.0, 100.0, 40.0, 100.0, 29.0, 70.0, 100.0, 71.0, 70.0, 100.0, 16.0, 100.0, 100.0, 58.0, 100.0, 100.0, 100.0, 100.0, 100.0", 0, 2.0, 1
|
||||
|
@@ -0,0 +1,2 @@
|
||||
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
|
||||
1, 65, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "65.0, 15.0, 65.0, 65.0, 15.0, 45.0", 3, "0.0, 25.0, 55.0, 40.0, 10.0, 0.0, 40.0, 45.0, 60.0", "100.0, 70.0, 60.0, 45.0, 80.0, 55.0, 100.0, 50.0, 100.0", 0, 2.0, 1
|
||||
|
@@ -0,0 +1,2 @@
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timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
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||||
1, 100, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 80.0", "0.25, 0.25", "8.0, 8.0", "0.1, 0.1", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "66.6, 66.6", "55, 35, 35, 55", 0.15, "15.0, 15.0, 50.0, 40.0, 15.0, 50.0", 1, "0.0, 35.0, 0.0", "50, 40.0, 60", 1, 2.0, 1
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|
@@ -0,0 +1,2 @@
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timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
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1, 65, 35.0, 0.1, 2.0, 6, 1, 1, "8.0, 8.0", "35.0, 35.0", "80.0, 50.0", "0.25, 1.0", "8.0, 25.0", "0.1, 0.02", "0.0, 0.0, 0.0", "100.0, 100.0, 100.0", "30.0, 80.0", "60, 20, 20, 30", 0.15, "90.0, 10.0, 50.0, 65.0, 15.0, 45.0", 4, "0.0, 30.0, 0.0, 70.0, 30.0, 0.0, 0.0, 60.0, 0.0, 55.0, 60.0, 0.0", "50.0, 40.0, 100.0, 100.0, 40.0, 100.0, 35.0, 70.0, 100.0, 100.0, 70.0, 100.0", 0, 2.0, 1
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xrotg.h</Path>
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<Type>GENERATED_SOURCE</Type>
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<File type="coderapp.internal.util.mfz.FileSpec">
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xzgeqp3.cpp</Path>
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||||
</File>
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<Type>GENERATED_SOURCE</Type>
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xzgeqp3.h</Path>
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<Type>GENERATED_SOURCE</Type>
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<File type="coderapp.internal.util.mfz.FileSpec">
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xzlarf.cpp</Path>
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</File>
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<Type>GENERATED_SOURCE</Type>
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<File type="coderapp.internal.util.mfz.FileSpec">
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xzlarf.h</Path>
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<File type="coderapp.internal.util.mfz.FileSpec">
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/xzlarfg.cpp</Path>
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<Path>/home/kdee/matlab/R2025a/extern/include/tmwtypes.h</Path>
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</File>
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<Type>GENERATED_SOURCE</Type>
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</Artifacts>
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<Artifacts id="167" type="coderapp.internal.build.mfz.CodegenArtifact">
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<File type="coderapp.internal.util.mfz.FileSpec">
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/examples/main.cpp</Path>
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</File>
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<Type>GENERATED_SOURCE</Type>
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<Path>/home/kdee/Desktop/miSim/aerpaw/codegen/examples/main.h</Path>
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||||
</File>
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||||
@@ -1099,7 +1188,7 @@
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||||
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<BuildFolder type="coderapp.internal.util.mfz.FileSpec"/>
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<Success>true</Success>
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||||
<Timestamp>2026-04-07T22:43:01</Timestamp>
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||||
</MainBuildResult>
|
||||
</coderapp.internal.mlc.mfz.MatlabCoderProjectState>
|
||||
</MF0>
|
||||
|
||||
+49
-4
@@ -7,7 +7,8 @@ coder.extrinsic('disp', 'readScenarioCsv');
|
||||
|
||||
% Maximum clients supported (one initial position per UAV)
|
||||
MAX_CLIENTS = 4;
|
||||
MAX_TARGETS = MAX_CLIENTS;
|
||||
% Two waypoints per UAV: altitude-staggered transit + final position
|
||||
MAX_TARGETS = MAX_CLIENTS * 2;
|
||||
|
||||
% Allocate targets array (MAX_TARGETS x 3)
|
||||
targets = zeros(MAX_TARGETS, 3);
|
||||
@@ -33,8 +34,31 @@ else
|
||||
numWaypoints = totalLoaded / int32(numClients);
|
||||
end
|
||||
|
||||
% In the compiled path, inject altitude-staggered transit waypoints so UAVs
|
||||
% are vertically separated while flying horizontally to their start positions.
|
||||
% ArduPilot reaches target altitude before horizontal movement, so UAV i is at
|
||||
% altitude (TRANSIT_ALT_BASE + (i-1)*TRANSIT_ALT_STEP) throughout its transit,
|
||||
% preventing collisions regardless of horizontal path geometry.
|
||||
% TRANSIT_ALT_STEP must exceed 2 * max(collisionRadius).
|
||||
% Waypoint 1: each UAV flies to (finalX, finalY) at its unique transit altitude.
|
||||
% Waypoint 2: each UAV adjusts to its actual target altitude.
|
||||
% These constants are also used for the altitude-staggered return before RTL.
|
||||
TRANSIT_ALT_BASE = 25.0; % must match drone.takeoff() altitude in uav_runner.py
|
||||
TRANSIT_ALT_STEP = 25; % vertical separation per UAV (m); must exceed 2*collisionRadius
|
||||
if ~coder.target('MATLAB')
|
||||
for ii = double(totalLoaded):-1:1
|
||||
transitRow = (ii - 1) * 2 + 1;
|
||||
finalRow = (ii - 1) * 2 + 2;
|
||||
finalPos = targets(ii, :);
|
||||
transitAlt = TRANSIT_ALT_BASE + (ii - 1) * TRANSIT_ALT_STEP;
|
||||
targets(finalRow, :) = finalPos;
|
||||
targets(transitRow, :) = [finalPos(1), finalPos(2), transitAlt];
|
||||
end
|
||||
numWaypoints = int32(2);
|
||||
end
|
||||
|
||||
% Load guidance scenario from CSV (parameters for guidance_step)
|
||||
NUM_SCENARIO_PARAMS = 45;
|
||||
NUM_SCENARIO_PARAMS = 48;
|
||||
MAX_OBSTACLES_CTRL = int32(8);
|
||||
scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
|
||||
obstacleMin = zeros(MAX_OBSTACLES_CTRL, 3);
|
||||
@@ -78,7 +102,7 @@ for w = 1:numWaypoints
|
||||
target = targets(targetIdx, :);
|
||||
|
||||
if coder.target('MATLAB')
|
||||
disp([datestr(now, 'HH:MM:SS'), ' Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
|
||||
disp(['Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
|
||||
num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]);
|
||||
else
|
||||
coder.ceval('sendTarget', int32(i), coder.ref(target));
|
||||
@@ -125,6 +149,10 @@ guidance_step(positions(1:numClients, :), true, ...
|
||||
|
||||
% Main guidance loop (event-triggered)
|
||||
for step = 1:MAX_GUIDANCE_STEPS
|
||||
if ~coder.target('MATLAB')
|
||||
coder.ceval('setGuidanceStep', int32(step), int32(MAX_GUIDANCE_STEPS));
|
||||
end
|
||||
|
||||
% Run one guidance step: feed current GPS positions in, get targets out
|
||||
nextPositions = guidance_step(positions(1:numClients, :), false, ...
|
||||
scenarioParams, obstacleMin, obstacleMax, numObstacles);
|
||||
@@ -135,7 +163,7 @@ for step = 1:MAX_GUIDANCE_STEPS
|
||||
if ~coder.target('MATLAB')
|
||||
coder.ceval('sendTarget', int32(i), coder.ref(target));
|
||||
else
|
||||
disp([datestr(now, 'HH:MM:SS'), ' [guidance] target UAV ', num2str(i), ': ', num2str(target)]);
|
||||
disp(['[step ', num2str(step), '] target UAV ', num2str(i), ': ', num2str(target)]);
|
||||
end
|
||||
end
|
||||
|
||||
@@ -164,9 +192,26 @@ if ~coder.target('MATLAB')
|
||||
% last guidance navigation and is back in sequential (ACK/READY) mode.
|
||||
coder.ceval('waitForAllMessageType', int32(numClients), ...
|
||||
int32(MESSAGE_TYPE.ACK));
|
||||
% Reset step counter so post-guidance logging carries no step prefix.
|
||||
coder.ceval('setGuidanceStep', int32(0), int32(MAX_GUIDANCE_STEPS));
|
||||
end
|
||||
% --------------------------------------------------------------------------
|
||||
|
||||
% Altitude-staggered return: separate UAVs vertically before issuing RTL,
|
||||
% mirroring the initial positioning stagger so UAVs transit laterally at
|
||||
% unique altitudes and cannot collide during the return flight.
|
||||
if ~coder.target('MATLAB')
|
||||
for i = 1:numClients
|
||||
transitAlt = TRANSIT_ALT_BASE + (double(i) - 1) * TRANSIT_ALT_STEP;
|
||||
target = [positions(i, 1), positions(i, 2), transitAlt];
|
||||
coder.ceval('sendTarget', int32(i), coder.ref(target));
|
||||
end
|
||||
coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.ACK));
|
||||
coder.ceval('waitForAllMessageType', int32(numClients), int32(MESSAGE_TYPE.READY));
|
||||
else
|
||||
disp('Altitude-staggered return (simulation): UAVs commanded to transit altitudes.');
|
||||
end
|
||||
|
||||
% Send RTL command to all clients
|
||||
for i = 1:numClients
|
||||
if coder.target('MATLAB')
|
||||
|
||||
+12
-2
@@ -29,6 +29,9 @@ function nextPositions = guidance_step(currentPositions, isInit, ...
|
||||
% 39-40 objectivePos
|
||||
% 41-44 objectiveVar (2x2, col-major)
|
||||
% 45 sensorPerformanceMinimum
|
||||
% 46 useDoubleIntegrator
|
||||
% 47 dampingCoeff
|
||||
% 48 useFixedTopology
|
||||
% obstacleMin (MAX_OBSTACLES × 3) double column-major obstacle corners (compiled path)
|
||||
% obstacleMax (MAX_OBSTACLES × 3) double
|
||||
% numObstacles (1,1) int32 actual obstacle count
|
||||
@@ -94,6 +97,9 @@ if isInit
|
||||
OBJECTIVE_GROUND_POS = scenarioParams(39:40);
|
||||
OBJECTIVE_VAR = reshape(scenarioParams(41:44), 2, 2);
|
||||
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(45);
|
||||
USE_DOUBLE_INTEGRATOR = logical(scenarioParams(46));
|
||||
DAMPING_COEFF = scenarioParams(47);
|
||||
USE_FIXED_TOPOLOGY = logical(scenarioParams(48));
|
||||
|
||||
% --- Build domain geometry ---
|
||||
dom = rectangularPrism;
|
||||
@@ -146,7 +152,8 @@ if isInit
|
||||
% --- Initialise simulation (plots and video disabled) ---
|
||||
sim = miSim;
|
||||
sim = sim.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
|
||||
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
|
||||
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
|
||||
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
|
||||
end
|
||||
|
||||
% On the init call return current positions unchanged
|
||||
@@ -176,7 +183,9 @@ else
|
||||
sim.timestepIndex = sim.timestepIndex + 1;
|
||||
|
||||
% 3. Update communications topology (Lesser Neighbour Assignment)
|
||||
if ~sim.useFixedTopology
|
||||
sim = sim.lesserNeighbor();
|
||||
end
|
||||
|
||||
% 4. Compute Voronoi partitioning
|
||||
sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
|
||||
@@ -184,7 +193,8 @@ else
|
||||
% 5. Unconstrained gradient-ascent step for each agent
|
||||
for ii = 1:size(sim.agents, 1)
|
||||
sim.agents{ii} = sim.agents{ii}.run(sim.domain, sim.partitioning, ...
|
||||
sim.timestepIndex, ii, sim.agents);
|
||||
sim.timestepIndex, ii, ...
|
||||
sim.useDoubleIntegrator, sim.dampingCoeff, sim.timestep, sim.optimizeSensorPointing);
|
||||
end
|
||||
|
||||
% 6. Apply CBF safety filter (collision / comms / domain constraints via QP)
|
||||
|
||||
@@ -16,6 +16,44 @@
|
||||
|
||||
static int serverSocket = -1;
|
||||
static std::vector<int> clientSockets;
|
||||
static int guidanceStep = 0;
|
||||
static int guidanceTotalSteps = 0;
|
||||
static struct timespec lastStepTime = {0, 0};
|
||||
|
||||
// During guidance returns "(%d/%d) "; outside guidance returns "HH:MM:SS ".
|
||||
static std::string logPrefix() {
|
||||
if (guidanceStep > 0) {
|
||||
char buf[32];
|
||||
snprintf(buf, sizeof(buf), "(%d/%d) ", guidanceStep, guidanceTotalSteps);
|
||||
return std::string(buf);
|
||||
}
|
||||
time_t now = time(nullptr);
|
||||
struct tm* lt = localtime(&now);
|
||||
char ts[16];
|
||||
strftime(ts, sizeof(ts), "%H:%M:%S", lt);
|
||||
return std::string(ts) + " ";
|
||||
}
|
||||
|
||||
void setGuidanceStep(int step, int totalSteps) {
|
||||
struct timespec now;
|
||||
clock_gettime(CLOCK_MONOTONIC, &now);
|
||||
|
||||
// From step 2 onward, elapsed = setGuidanceStep(N-1) → setGuidanceStep(N),
|
||||
// which spans the full prior iteration: guidance computation + target send
|
||||
// + flight + position request/receive.
|
||||
if (step > 1 && lastStepTime.tv_sec != 0) {
|
||||
double elapsed = (now.tv_sec - lastStepTime.tv_sec)
|
||||
+ (now.tv_nsec - lastStepTime.tv_nsec) * 1e-9;
|
||||
guidanceStep = step;
|
||||
guidanceTotalSteps = totalSteps;
|
||||
std::cout << logPrefix() << "Iteration duration: " << elapsed << " s\n";
|
||||
} else {
|
||||
guidanceStep = step;
|
||||
guidanceTotalSteps = totalSteps;
|
||||
}
|
||||
|
||||
lastStepTime = now;
|
||||
}
|
||||
|
||||
void initSockets() {}
|
||||
void cleanupSockets() {}
|
||||
@@ -186,7 +224,10 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
|
||||
// 35-37: domainMax (east, north, up)
|
||||
// 38-39: objectivePos (east, north)
|
||||
// 40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
|
||||
// 44 : sensorPerformanceMinimum
|
||||
// 44 : sensorPerformanceMinimum (CSV column 18)
|
||||
// 45 : useDoubleIntegrator (CSV column 23; 0=single-integrator, 1=double-integrator)
|
||||
// 46 : dampingCoeff (CSV column 24)
|
||||
// 47 : useFixedTopology (CSV column 25; 0=dynamic lesser-neighbor, 1=fixed)
|
||||
// Returns 1 on success, 0 on failure.
|
||||
int loadScenario(const char* filename, double* params) {
|
||||
char line[4096];
|
||||
@@ -198,8 +239,8 @@ int loadScenario(const char* filename, double* params) {
|
||||
|
||||
char* fields[32];
|
||||
int nf = splitCSVRow(copy, fields, 32);
|
||||
if (nf < 19) {
|
||||
fprintf(stderr, "loadScenario: expected >=19 columns, got %d\n", nf);
|
||||
if (nf < 26) {
|
||||
fprintf(stderr, "loadScenario: expected >=26 columns, got %d\n", nf);
|
||||
return 0;
|
||||
}
|
||||
|
||||
@@ -290,6 +331,24 @@ int loadScenario(const char* filename, double* params) {
|
||||
params[44] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// useDoubleIntegrator: column 23
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[23], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[45] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// dampingCoeff: column 24
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[24], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[46] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// useFixedTopology: column 25
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[25], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[47] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g]\n",
|
||||
params[32], params[33], params[34], params[35], params[36], params[37]);
|
||||
return 1;
|
||||
@@ -430,18 +489,22 @@ static const char* messageTypeName(uint8_t msgType) {
|
||||
}
|
||||
}
|
||||
|
||||
// Send a single-byte message type to a client
|
||||
int sendMessageType(int clientId, int msgType) {
|
||||
// Send a single-byte message type to a client (no logging)
|
||||
static int sendMessageTypeRaw(int clientId, int msgType) {
|
||||
if (clientId <= 0 || clientId > (int)clientSockets.size()) return 0;
|
||||
|
||||
uint8_t msg = (uint8_t)msgType;
|
||||
ssize_t sent = send(clientSockets[clientId - 1], &msg, 1, 0);
|
||||
if (sent != 1) {
|
||||
std::cerr << "Send failed for client " << clientId << "\n";
|
||||
return 0;
|
||||
}
|
||||
return 1;
|
||||
}
|
||||
|
||||
std::cout << "Sent " << messageTypeName(msg) << " to client " << clientId << "\n";
|
||||
// Send a single-byte message type to a client
|
||||
int sendMessageType(int clientId, int msgType) {
|
||||
if (!sendMessageTypeRaw(clientId, msgType)) return 0;
|
||||
std::cout << logPrefix() << "Sent " << messageTypeName((uint8_t)msgType) << " to client " << clientId << "\n";
|
||||
return 1;
|
||||
}
|
||||
|
||||
@@ -460,13 +523,7 @@ int sendTarget(int clientId, const double* coords) {
|
||||
return 0;
|
||||
}
|
||||
|
||||
// Timestamp
|
||||
time_t now = time(nullptr);
|
||||
struct tm* lt = localtime(&now);
|
||||
char ts[16];
|
||||
strftime(ts, sizeof(ts), "%H:%M:%S", lt);
|
||||
|
||||
std::cout << ts << " Sent TARGET to client " << clientId << ": "
|
||||
std::cout << logPrefix() << "Sent TARGET to client " << clientId << ": "
|
||||
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
|
||||
return 1;
|
||||
}
|
||||
@@ -514,31 +571,36 @@ int waitForAllMessageType(int numClients, int expectedType) {
|
||||
return 0;
|
||||
}
|
||||
|
||||
std::cout << "Received " << messageTypeName(msgType) << " from client " << (i + 1) << "\n";
|
||||
|
||||
if (msgType == expected) {
|
||||
completed[i] = true;
|
||||
completedCount++;
|
||||
} else {
|
||||
std::cerr << logPrefix() << "Unexpected " << messageTypeName(msgType)
|
||||
<< " from client " << (i + 1)
|
||||
<< " (expected " << messageTypeName(expected) << ")\n";
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
std::cout << logPrefix() << "Received " << messageTypeName(expected) << " from all clients\n";
|
||||
return 1;
|
||||
}
|
||||
|
||||
// Broadcast GUIDANCE_TOGGLE to all clients
|
||||
void sendGuidanceToggle(int numClients) {
|
||||
for (int i = 1; i <= numClients; i++) {
|
||||
sendMessageType(i, 6); // GUIDANCE_TOGGLE = 6
|
||||
sendMessageTypeRaw(i, 6); // GUIDANCE_TOGGLE = 6
|
||||
}
|
||||
std::cout << logPrefix() << "Sent GUIDANCE_TOGGLE to clients\n";
|
||||
}
|
||||
|
||||
// Send REQUEST_POSITION to all clients
|
||||
int sendRequestPositions(int numClients) {
|
||||
for (int i = 1; i <= numClients; i++) {
|
||||
if (!sendMessageType(i, 7)) return 0; // REQUEST_POSITION = 7
|
||||
if (!sendMessageTypeRaw(i, 7)) return 0; // REQUEST_POSITION = 7
|
||||
}
|
||||
std::cout << logPrefix() << "Sent REQUEST_POSITION to clients\n";
|
||||
return 1;
|
||||
}
|
||||
|
||||
@@ -573,7 +635,7 @@ int recvPositions(int numClients, double* positions, int maxClients) {
|
||||
positions[i + 1 * maxClients] = coords[1]; // north (y)
|
||||
positions[i + 2 * maxClients] = coords[2]; // up (z)
|
||||
|
||||
std::cout << "Position from client " << (i + 1) << ": "
|
||||
std::cout << logPrefix() << "Position from client " << (i + 1) << ": "
|
||||
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
|
||||
}
|
||||
return 1;
|
||||
|
||||
@@ -30,7 +30,10 @@ int loadTargets(const char* filename, double* targets, int maxClients);
|
||||
// 38-39 objectivePos
|
||||
// 40-43 objectiveVar (2x2 col-major)
|
||||
// 44 sensorPerformanceMinimum
|
||||
#define NUM_SCENARIO_PARAMS 45
|
||||
// 45 useDoubleIntegrator (0=single-integrator, 1=double-integrator)
|
||||
// 46 dampingCoeff
|
||||
// 47 useFixedTopology (0=dynamic lesser-neighbor, 1=fixed)
|
||||
#define NUM_SCENARIO_PARAMS 48
|
||||
#define MAX_CLIENTS_PER_PARAM 4
|
||||
// Maximum number of obstacles (upper bound for pre-allocated arrays).
|
||||
#define MAX_OBSTACLES 8
|
||||
@@ -59,6 +62,7 @@ int sendTarget(int clientId, const double* coords);
|
||||
int waitForAllMessageType(int numClients, int expectedType);
|
||||
|
||||
// Guidance loop operations
|
||||
void setGuidanceStep(int step, int totalSteps); // call at the top of each guidance iteration
|
||||
void sendGuidanceToggle(int numClients);
|
||||
int sendRequestPositions(int numClients);
|
||||
int recvPositions(int numClients, double* positions, int maxClients); // column-major maxClients x 3
|
||||
|
||||
@@ -13,3 +13,4 @@ cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
|
||||
|
||||
echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
|
||||
echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"
|
||||
echo "REMEMBER! Manually copy startVehicle_controller.sh to ~/Profiles/ProfileScripts/Vehicle/startVehicle.sh on the fixed node"
|
||||
@@ -0,0 +1,28 @@
|
||||
function controller = controllerAnalysis(resultsPath)
|
||||
arguments (Input)
|
||||
resultsPath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
controller table;
|
||||
end
|
||||
|
||||
% Measure intervals between issuing commands from the controller
|
||||
% (make sure this is ~4-5 seconds at minimum to avoid overwhelming the UAV autopilot)
|
||||
r = dir(resultsPath);
|
||||
controllerPath = fullfile(r(startsWith({r.name}, 'controller_')).folder, r(startsWith({r.name}, 'controller_')).name);
|
||||
controllerPath = dir(controllerPath);
|
||||
controllerPath = fullfile(controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).folder, controllerPath(endsWith({controllerPath.name}, '_controller_log.txt')).name);
|
||||
controller = readControllerLogs(controllerPath);
|
||||
rpIdx = startsWith(controller.message, "Iteration duration: ");
|
||||
s = split(controller.message(rpIdx), "Iteration duration: ");
|
||||
s = split(s(:, 2), ' s');
|
||||
s = duration(strcat("00:", s(:, 1)), "InputFormat", "mm:ss.SSS");
|
||||
s.Format = "mm:ss.SSS";
|
||||
fprintf("Minimum command spacing: %2.3f seconds\n", seconds(min(s)));
|
||||
fprintf("Maximum command spacing: %2.3f seconds\n", seconds(max(s)));
|
||||
fprintf("Mean command spacing: %2.3f seconds\n", seconds(mean(s)));
|
||||
fprintf("Median command spacing: %2.3f seconds\n", seconds(median(s)));
|
||||
if seconds(min(s)) < 4
|
||||
warning("Minimum command spacing %2.3f questionably short for AERPAW", seconds(min(s)));
|
||||
end
|
||||
end
|
||||
@@ -1,7 +1,8 @@
|
||||
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
|
||||
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
|
||||
arguments (Input)
|
||||
logDirs (1, 1) string;
|
||||
seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
|
||||
plotWholeFlight (1, 1) logical = false;
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) matlab.ui.Figure;
|
||||
@@ -28,6 +29,7 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
|
||||
logDirs = dir(logDirs);
|
||||
logDirs = logDirs(3:end);
|
||||
logDirs = logDirs([logDirs.isdir] == 1);
|
||||
logDirs = logDirs(~startsWith({logDirs.name}, "controller_"));
|
||||
|
||||
G = cell(size(logDirs));
|
||||
for ii = 1:size(logDirs, 1)
|
||||
@@ -48,8 +50,10 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
|
||||
stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
|
||||
|
||||
% % Plot whole flight, including setup/cleanup
|
||||
% startIdx = 1;
|
||||
% stopIdx = length(verticalSpeed);
|
||||
if plotWholeFlight
|
||||
startIdx = 1;
|
||||
stopIdx = length(verticalSpeed);
|
||||
end
|
||||
|
||||
% Convert LLA trajectory data to ENU for external analysis
|
||||
% NaN out entries outside the algorithm flight range so they don't plot
|
||||
@@ -58,6 +62,27 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
|
||||
enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
|
||||
G{ii} = [G{ii}, enu];
|
||||
|
||||
% Do crude comparison of pairwise distances between this UAV and
|
||||
% all previous UAVs
|
||||
for jj = 1:(ii - 1)
|
||||
Ai = G{ii}(:, [1, end-2:end]);
|
||||
Aj = G{jj}(:, [1, end-2:end]);
|
||||
|
||||
% Trim data to match sizes
|
||||
idx = min([size(Ai, 1), size(Aj, 1)]);
|
||||
Ai = Ai(1:idx, :); Aj = Aj(1:idx, :);
|
||||
|
||||
pos_i = [Ai.East, Ai.North, Ai.Up];
|
||||
pos_j = [Aj.East, Aj.North, Aj.Up];
|
||||
d = vecnorm(pos_i - pos_j, 2, 2);
|
||||
d = d(~isnan(d));
|
||||
|
||||
fprintf("Minimum distance between agents %d and %d is %2.3f\n", ii, jj, min(d));
|
||||
if min(d) < 6
|
||||
warning("Minimum distance between agents %d and %d of %2.3f is questionable for AERPAW", ii, jj, min(d));
|
||||
end
|
||||
end
|
||||
|
||||
% Plot recorded trajectory over specified range of indices
|
||||
geoplot3(gf, G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx) + seaToGroundLevel, c(mod(ii, length(c))), 'LineWidth', 2, "MarkerSize", 5);
|
||||
end
|
||||
|
||||
@@ -1,9 +1,12 @@
|
||||
function [f, R] = plotRadioLogs(resultsPath)
|
||||
function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
|
||||
arguments (Input)
|
||||
resultsPath (1, 1) string;
|
||||
G cell = {};
|
||||
tLim (1, 2) datetime = [datetime(-Inf, 'ConvertFrom', 'datenum'), datetime(Inf, 'ConvertFrom', 'datenum')];
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) matlab.ui.Figure;
|
||||
fDist (1, 1) matlab.ui.Figure;
|
||||
R cell;
|
||||
end
|
||||
|
||||
@@ -40,11 +43,44 @@ function [f, R] = plotRadioLogs(resultsPath)
|
||||
|
||||
metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
|
||||
yLabels = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
|
||||
nMetrics = numel(metricNames);
|
||||
|
||||
% --- Time-based figure ---
|
||||
f = figure;
|
||||
tl = tiledlayout(numel(metricNames), 1, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||
tl = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||
|
||||
for mi = 1:numel(metricNames)
|
||||
% Distance vs time tile (first)
|
||||
ax = nexttile(tl);
|
||||
hold(ax, 'on'); grid(ax, 'on');
|
||||
legendEntries = string.empty;
|
||||
ci = 1;
|
||||
if ~isempty(G)
|
||||
for rxIdx = 1:nUAV
|
||||
tbl = R{rxIdx};
|
||||
txIDs = unique(tbl.TxUAVID);
|
||||
for ti = 1:numel(txIDs)
|
||||
txID = txIDs(ti);
|
||||
rows = tbl(tbl.TxUAVID == txID, :);
|
||||
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
|
||||
if isempty(rows), continue; end
|
||||
[~, ia] = unique(rows.Timestamp);
|
||||
[radioPt, dist] = pairDist(rows(ia, :), G);
|
||||
if isempty(dist) || all(isnan(dist)), continue; end
|
||||
valid = ~isnan(dist);
|
||||
si = mod(ci - 1, numel(styles)) + 1;
|
||||
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
|
||||
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
|
||||
ci = ci + 1;
|
||||
end
|
||||
end
|
||||
end
|
||||
ylabel(ax, 'Distance (m)');
|
||||
xlabel(ax, 'Time');
|
||||
legend(ax, legendEntries, 'Location', 'best');
|
||||
hold(ax, 'off');
|
||||
|
||||
for mi = 1:nMetrics
|
||||
ax = nexttile(tl);
|
||||
hold(ax, 'on');
|
||||
grid(ax, 'on');
|
||||
@@ -57,23 +93,32 @@ function [f, R] = plotRadioLogs(resultsPath)
|
||||
for ti = 1:numel(txIDs)
|
||||
txID = txIDs(ti);
|
||||
rows = tbl(tbl.TxUAVID == txID, :);
|
||||
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
|
||||
vals = rows.(metricNames(mi));
|
||||
valid = ~isnan(vals);
|
||||
rows = rows(valid, :);
|
||||
vals = vals(valid);
|
||||
|
||||
% Skip if all NaN for this metric
|
||||
if all(isnan(vals))
|
||||
if isempty(rows)
|
||||
continue;
|
||||
end
|
||||
|
||||
si = mod(ci - 1, numel(styles)) + 1;
|
||||
plot(ax, rows.Timestamp, vals, styles(si), ...
|
||||
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
|
||||
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, tbl.RxUAVID(1)); %#ok<AGROW>
|
||||
|
||||
% Median per 1/3-second time bin
|
||||
[t_med, v_med] = timeBinMedian(posixtime(rows.Timestamp), vals, 1/3);
|
||||
plot(ax, datetime(t_med, 'ConvertFrom', 'posixtime'), v_med, '-', ...
|
||||
'Color', 'r', 'LineWidth', 2);
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, tbl.RxUAVID(1)); %#ok<AGROW>
|
||||
ci = ci + 1;
|
||||
end
|
||||
end
|
||||
|
||||
ylabel(ax, yLabels(mi));
|
||||
if mi == numel(metricNames)
|
||||
if mi == nMetrics
|
||||
xlabel(ax, 'Time');
|
||||
end
|
||||
legend(ax, legendEntries, 'Location', 'best');
|
||||
@@ -81,4 +126,134 @@ function [f, R] = plotRadioLogs(resultsPath)
|
||||
end
|
||||
|
||||
title(tl, 'Radio Channel Metrics');
|
||||
|
||||
% --- Distance-based figure ---
|
||||
fDist = figure;
|
||||
|
||||
if isempty(G)
|
||||
return;
|
||||
end
|
||||
|
||||
tl2 = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||
|
||||
% Distance vs time tile (first)
|
||||
ax = nexttile(tl2);
|
||||
hold(ax, 'on'); grid(ax, 'on');
|
||||
legendEntries = string.empty;
|
||||
ci = 1;
|
||||
for rxIdx = 1:nUAV
|
||||
tbl = R{rxIdx};
|
||||
txIDs = unique(tbl.TxUAVID);
|
||||
for ti = 1:numel(txIDs)
|
||||
txID = txIDs(ti);
|
||||
rows = tbl(tbl.TxUAVID == txID, :);
|
||||
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
|
||||
if isempty(rows), continue; end
|
||||
[~, ia] = unique(rows.Timestamp);
|
||||
[radioPt, dist] = pairDist(rows(ia, :), G);
|
||||
if isempty(dist) || all(isnan(dist)), continue; end
|
||||
valid = ~isnan(dist);
|
||||
si = mod(ci - 1, numel(styles)) + 1;
|
||||
plot(ax, datetime(radioPt(valid), 'ConvertFrom', 'posixtime'), dist(valid), ...
|
||||
styles(si), 'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
|
||||
ci = ci + 1;
|
||||
end
|
||||
end
|
||||
ylabel(ax, 'Distance (m)');
|
||||
xlabel(ax, 'Time');
|
||||
legend(ax, legendEntries, 'Location', 'best');
|
||||
hold(ax, 'off');
|
||||
|
||||
for mi = 1:nMetrics
|
||||
ax = nexttile(tl2);
|
||||
hold(ax, 'on');
|
||||
grid(ax, 'on');
|
||||
|
||||
legendEntries = string.empty;
|
||||
ci = 1;
|
||||
for rxIdx = 1:nUAV
|
||||
tbl = R{rxIdx};
|
||||
txIDs = unique(tbl.TxUAVID);
|
||||
for ti = 1:numel(txIDs)
|
||||
txID = txIDs(ti);
|
||||
rows = tbl(tbl.TxUAVID == txID, :);
|
||||
|
||||
if isempty(rows)
|
||||
continue;
|
||||
end
|
||||
|
||||
rows = rows(rows.Timestamp >= tLim(1) & rows.Timestamp <= tLim(2), :);
|
||||
if isempty(rows)
|
||||
continue;
|
||||
end
|
||||
|
||||
vals = rows.(metricNames(mi));
|
||||
valid = ~isnan(vals);
|
||||
rows = rows(valid, :);
|
||||
vals = vals(valid);
|
||||
|
||||
if isempty(rows)
|
||||
continue;
|
||||
end
|
||||
|
||||
[radioPt, dist] = pairDist(rows, G);
|
||||
if isempty(dist) || all(isnan(dist)), continue; end
|
||||
|
||||
% Drop points where GPS interpolation returned NaN
|
||||
validDist = ~isnan(dist);
|
||||
rowTs = radioPt(validDist);
|
||||
dist = dist(validDist);
|
||||
vals = vals(validDist);
|
||||
|
||||
si = mod(ci - 1, numel(styles)) + 1;
|
||||
scatter(ax, dist, vals, 9, colors(ci, :), strrep(styles(si), "-", ""), 'filled');
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d", txID, rows.RxUAVID(1)); %#ok<AGROW>
|
||||
|
||||
% Median per 1/3-second time bin, plotted against median distance
|
||||
[~, dv_med] = timeBinMedian(rowTs, [dist, vals], 1/3);
|
||||
[d_med, si_sort] = sort(dv_med(:, 1));
|
||||
v_med = dv_med(si_sort, 2);
|
||||
plot(ax, d_med, v_med, '-', 'Color', 'r', 'LineWidth', 2);
|
||||
legendEntries(end+1) = sprintf("TX %d → RX %d (median)", txID, rows.RxUAVID(1)); %#ok<AGROW>
|
||||
ci = ci + 1;
|
||||
end
|
||||
end
|
||||
|
||||
ylabel(ax, yLabels(mi));
|
||||
if mi == nMetrics
|
||||
xlabel(ax, 'Distance (m)');
|
||||
end
|
||||
legend(ax, legendEntries, 'Location', 'best');
|
||||
hold(ax, 'off');
|
||||
end
|
||||
|
||||
title(tl2, 'Radio Channel Metrics vs Distance');
|
||||
end
|
||||
|
||||
|
||||
function [radioPt, dist] = pairDist(rows, G)
|
||||
% Interpolate GPS-based inter-UAV distance at each row's timestamp.
|
||||
radioPt = []; dist = [];
|
||||
txGpsIdx = double(rows.TxUAVID(1)) + 1;
|
||||
rxGpsIdx = double(rows.RxUAVID(1)) + 1;
|
||||
if txGpsIdx > numel(G) || rxGpsIdx > numel(G), return; end
|
||||
Gtx = G{txGpsIdx};
|
||||
Grx = G{rxGpsIdx};
|
||||
if ~ismember('East', Gtx.Properties.VariableNames) || ...
|
||||
~ismember('East', Grx.Properties.VariableNames), return; end
|
||||
txTs = Gtx.Timestamp; txTs.TimeZone = '';
|
||||
rxTs = Grx.Timestamp; rxTs.TimeZone = '';
|
||||
txPt = posixtime(txTs);
|
||||
rxPt = posixtime(rxTs);
|
||||
radioPt = posixtime(rows.Timestamp);
|
||||
validTx = ~isnan(Gtx.East);
|
||||
validRx = ~isnan(Grx.East);
|
||||
txE = interp1(txPt(validTx), Gtx.East(validTx), radioPt, 'linear', NaN);
|
||||
txN = interp1(txPt(validTx), Gtx.North(validTx), radioPt, 'linear', NaN);
|
||||
txU = interp1(txPt(validTx), Gtx.Up(validTx), radioPt, 'linear', NaN);
|
||||
rxE = interp1(rxPt(validRx), Grx.East(validRx), radioPt, 'linear', NaN);
|
||||
rxN = interp1(rxPt(validRx), Grx.North(validRx), radioPt, 'linear', NaN);
|
||||
rxU = interp1(rxPt(validRx), Grx.Up(validRx), radioPt, 'linear', NaN);
|
||||
dist = vecnorm([txE - rxE, txN - rxN, txU - rxU], 2, 2);
|
||||
end
|
||||
@@ -0,0 +1,32 @@
|
||||
function T2 = readControllerLogs(filepath)
|
||||
arguments (Input)
|
||||
filepath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
T2 table;
|
||||
end
|
||||
assert(isfile(filepath), "File not found at %s", filepath);
|
||||
|
||||
T = readtable(filepath, 'VariableNamingRule', 'preserve');
|
||||
s = split(T.(T.Properties.VariableNames{1}), ']');
|
||||
s2 = strip(s(startsWith(s(:, 2), " ("), 1), 'left', '[');
|
||||
d = datetime(s2, "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS")';
|
||||
it = s(startsWith(s(:, 2), " ("), 2);
|
||||
it = str2double(strip(strip(it, 'left'), 'left', '('));
|
||||
T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", T.Var7));
|
||||
T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = [];
|
||||
msg = T.(T.Properties.VariableNames{2});
|
||||
msg = msg(startsWith(s(:, 2), " ("), :);
|
||||
s3 = split(msg, ') ');
|
||||
s3 = s3(:, 2);
|
||||
msg = append(s3, T.Var3(startsWith(s(:, 2), " (")));
|
||||
T2 = table(it, d', msg, 'VariableNames', ["iteration", "timestamp", "message"]);
|
||||
% T.Var1 = datetime(strip(strip(append(T.Var1, " ", T.Var2), 'left', '['), 'right', ']'), "InputFormat", "yyyy-MM-dd HH:mm:ss.SSSSSS");
|
||||
% T.Var2 = [];
|
||||
% T.Var3 = strip(append(T.Var3, " ", T.Var4, " ", T.Var5, " ", T.Var6, " ", string(T.Var7), " ", T.Var8, " ", T.Var9));
|
||||
% T.Var4 = []; T.Var5 = []; T.Var6 = []; T.Var7 = []; T.Var8 = []; T.Var9 = [];
|
||||
% T.Properties.VariableNames{1} = 'timestamp';
|
||||
% T.Properties.VariableNames{2} = 'message';
|
||||
|
||||
% T(ismissing(T.message), :) = [];
|
||||
end
|
||||
@@ -2,7 +2,6 @@ function R = readRadioLogs(logPath)
|
||||
arguments (Input)
|
||||
logPath (1, 1) string {isfolder(logPath)};
|
||||
end
|
||||
|
||||
arguments (Output)
|
||||
R (:, 8) table;
|
||||
end
|
||||
@@ -31,14 +30,26 @@ function R = readRadioLogs(logPath)
|
||||
end
|
||||
|
||||
fid = fopen(filepath, 'r');
|
||||
% Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value)
|
||||
for k = 1:3
|
||||
fgetl(fid);
|
||||
% Skip header lines: some files have 2 tail-error lines + 1 column
|
||||
% header ("tx_uav_id,value"), others start with data immediately.
|
||||
% Read until a line that looks like a data record, then rewind to it.
|
||||
dataPattern = '^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+\] [-\d]';
|
||||
linePos = ftell(fid);
|
||||
while true
|
||||
line = fgetl(fid);
|
||||
if ~ischar(line)
|
||||
break; % EOF
|
||||
end
|
||||
if ~isempty(regexp(line, dataPattern, 'once'))
|
||||
fseek(fid, linePos, 'bof'); % rewind to start of this line
|
||||
break;
|
||||
end
|
||||
linePos = ftell(fid);
|
||||
end
|
||||
data = textscan(fid, '[%26c] %d,%f');
|
||||
fclose(fid);
|
||||
|
||||
ts = datetime(data{1}, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
|
||||
ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
|
||||
txId = int32(data{2});
|
||||
val = data{3};
|
||||
|
||||
@@ -59,6 +70,40 @@ function R = readRadioLogs(logPath)
|
||||
|
||||
R = sortrows(R, "Timestamp");
|
||||
|
||||
% Reconstruct per-measurement timestamps within GNURadio processing batches.
|
||||
% The flowgraph accumulates one full PN sequence (4095 chips at samp_rate/sps)
|
||||
% per measurement, but outputs the whole batch simultaneously with a single
|
||||
% wall-clock timestamp. We reassign timestamps by counting backward from the
|
||||
% batch processing time at the known PN period interval.
|
||||
pn_period = 4095 / (2e6 / 16); % 32.76 ms per PN correlation period
|
||||
|
||||
for txId = unique(R.TxUAVID)'
|
||||
rows = find(R.TxUAVID == txId);
|
||||
if numel(rows) < 2, continue; end
|
||||
|
||||
dt = seconds(diff(R.Timestamp(rows)));
|
||||
break_pos = [1; find(dt > 0.5) + 1];
|
||||
end_pos = [break_pos(2:end) - 1; numel(rows)];
|
||||
|
||||
for b = 1:numel(break_pos)
|
||||
idx = rows(break_pos(b) : end_pos(b));
|
||||
batch_ts = posixtime(R.Timestamp(idx));
|
||||
t_ref = max(batch_ts);
|
||||
|
||||
% Multiple metric files share the same processing timestamp for
|
||||
% each PN period, so group by unique original timestamp rather
|
||||
% than treating every row as a separate PN period.
|
||||
[~, ~, group_id] = unique(batch_ts);
|
||||
n_groups = max(group_id);
|
||||
new_ts = t_ref - (n_groups - 1 : -1 : 0)' * pn_period;
|
||||
|
||||
for g = 1:n_groups
|
||||
R.Timestamp(idx(group_id == g)) = ...
|
||||
datetime(new_ts(g), 'ConvertFrom', 'posixtime');
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
% Remove rows during defined guard period between TDM shifts
|
||||
R(R.TxUAVID == -1, :) = [];
|
||||
|
||||
|
||||
@@ -1,12 +1,16 @@
|
||||
%% Plot AERPAW logs (trajectory, radio)
|
||||
resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "two_around_wall"); % Define path to results copied from AERPAW platform
|
||||
|
||||
% Check timeline in controller logs
|
||||
controller = controllerAnalysis(resultsPath);
|
||||
|
||||
% Plot GPS logged data and scenario information (domain, objective, obstacles)
|
||||
seaToGroundLevel = 110; % measured approximately from USGS national map viewer
|
||||
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
|
||||
plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
|
||||
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
|
||||
|
||||
% Plot radio statistics
|
||||
[fRadio, R] = plotRadioLogs(resultsPath);
|
||||
% Plot radio statistics (time-based and distance-based)
|
||||
[fRadio, fRadioDist, R] = plotRadioLogs(resultsPath, G, controller.timestamp([1, end]));
|
||||
|
||||
%% Run simulation
|
||||
% Run miSim using same AERPAW scenario definition CSV
|
||||
@@ -21,7 +25,7 @@ makeVideo = true;
|
||||
% Define scenario according to CSV specification
|
||||
domain = rectangularPrism;
|
||||
domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
|
||||
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
|
||||
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [1, 2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
|
||||
|
||||
agents = cell(size(params.initialPositions, 2) / 3, 1);
|
||||
for ii = 1:size(agents, 1)
|
||||
@@ -33,7 +37,7 @@ for ii = 1:size(agents, 1)
|
||||
collisionGeometry = spherical;
|
||||
collisionGeometry = collisionGeometry.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), params.collisionRadius(ii), REGION_TYPE.COLLISION, sprintf("Agent %d collision geometry", ii));
|
||||
|
||||
agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, sprintf("Agent %d", ii), plotCommsGeometry);
|
||||
agents{ii} = agents{ii}.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), collisionGeometry, sensorModel, params.comRange(ii), params.maxIter, params.initialStepSize, 5.0, sprintf("Agent %d", ii), plotCommsGeometry);
|
||||
end
|
||||
|
||||
% Create obstacles
|
||||
@@ -60,9 +64,12 @@ copyobj(sim.f.Children, comparison);
|
||||
|
||||
% Plot trajectories on top
|
||||
for ii = 1:size(G, 1)
|
||||
gpsTimes = G{ii}.Timestamp;
|
||||
gpsTimes.TimeZone = '';
|
||||
inRange = gpsTimes >= controller.timestamp(1) & gpsTimes <= controller.timestamp(end);
|
||||
for jj = 1:size(sim.spatialPlotIndices, 2)
|
||||
hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "on");
|
||||
plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East, G{ii}.North, G{ii}.Up + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
|
||||
plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East(inRange), G{ii}.North(inRange), G{ii}.Up(inRange) + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
|
||||
hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "off");
|
||||
end
|
||||
end
|
||||
@@ -0,0 +1,29 @@
|
||||
function [t_med, v_med] = timeBinMedian(t, v, binWidth)
|
||||
% Compute median of each column of v within fixed-width time bins.
|
||||
%
|
||||
% t - (N,1) posixtime values
|
||||
% v - (N,K) data matrix; one column per quantity
|
||||
% binWidth - scalar bin width in seconds
|
||||
%
|
||||
% t_med - (B,1) median time of each non-empty bin
|
||||
% v_med - (B,K) median of each column per non-empty bin
|
||||
|
||||
edges = (floor(min(t) / binWidth) * binWidth) : binWidth : ...
|
||||
(floor(max(t) / binWidth) * binWidth + binWidth);
|
||||
bins = discretize(t, edges);
|
||||
nBins = numel(edges) - 1;
|
||||
K = size(v, 2);
|
||||
|
||||
t_all = NaN(nBins, 1);
|
||||
v_all = NaN(nBins, K);
|
||||
for bi = 1:nBins
|
||||
mask = bins == bi;
|
||||
if ~any(mask), continue; end
|
||||
t_all(bi) = median(t(mask));
|
||||
v_all(bi,:) = median(v(mask,:), 1);
|
||||
end
|
||||
|
||||
ok = ~isnan(t_all);
|
||||
t_med = t_all(ok);
|
||||
v_med = v_all(ok, :);
|
||||
end
|
||||
@@ -9,6 +9,8 @@ classdef cone
|
||||
center = NaN;
|
||||
radius = NaN;
|
||||
height = NaN;
|
||||
tilt = 0; % degrees, 0=nadir 90=horizon
|
||||
azimuth = 0; % degrees, 0=+Y 90=+X clockwise
|
||||
|
||||
% Plotting
|
||||
surface;
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
function obj = initialize(obj, center, radius, height, tag, label)
|
||||
function obj = initialize(obj, center, radius, height, tag, label, tilt, azimuth)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "cone")};
|
||||
center (1, 3) double;
|
||||
@@ -6,6 +6,8 @@ function obj = initialize(obj, center, radius, height, tag, label)
|
||||
height (1, 1) double;
|
||||
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
|
||||
label (1, 1) string = "";
|
||||
tilt (1, 1) double = 0;
|
||||
azimuth (1, 1) double = 0;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "cone")};
|
||||
@@ -16,4 +18,6 @@ function obj = initialize(obj, center, radius, height, tag, label)
|
||||
obj.height = height;
|
||||
obj.tag = tag;
|
||||
obj.label = label;
|
||||
obj.tilt = tilt;
|
||||
obj.azimuth = azimuth;
|
||||
end
|
||||
@@ -21,6 +21,17 @@ function [obj, f] = plot(obj, ind, f, maxAlt)
|
||||
% Scale to match height
|
||||
Z = Z * maxAlt;
|
||||
|
||||
% Rotate mesh around apex to match boresight tilt and azimuth.
|
||||
% Apex sits at [0, 0, maxAlt] before center translation.
|
||||
% Convention: tilt 0=nadir, 90=horizon; azimuth 0=+Y, 90=+X, clockwise.
|
||||
Ry = [cosd(obj.tilt), 0, -sind(obj.tilt); 0, 1, 0; sind(obj.tilt), 0, cosd(obj.tilt)];
|
||||
Rz = [sind(obj.azimuth), -cosd(obj.azimuth), 0; cosd(obj.azimuth), sind(obj.azimuth), 0; 0, 0, 1];
|
||||
R = Rz * Ry;
|
||||
pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
|
||||
X = reshape(pts(1, :), size(X));
|
||||
Y = reshape(pts(2, :), size(Y));
|
||||
Z = reshape(pts(3, :) + maxAlt, size(Z));
|
||||
|
||||
% Move to center location
|
||||
X = X + obj.center(1);
|
||||
Y = Y + obj.center(2);
|
||||
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="test"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="test_rfSensor.m" type="File"/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
+1
-1
@@ -1,2 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
<Info location="plot.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="clearRssCache.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="rfSensor.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="plotParameters.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="plotPerformance.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="halfAngle.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="computePointToPoints.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="sensorPerformance.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="transmitterGain.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="initialize.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
+1
-1
@@ -1,2 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
<Info location="RSS.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="pathLoss.m" type="File"/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="initializeFromInits.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="plotFromSimHist.m" type="File"/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="readControllerLogs.m" type="File"/>
|
||||
@@ -0,0 +1,6 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="controllerAnalysis.m" type="File"/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
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Reference in New Issue
Block a user