Compare commits
47 Commits
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| aed1924297 | |||
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| 8c5c315380 | |||
| b444e44d33 |
@@ -48,7 +48,6 @@ sandbox/*
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# Figures
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*.fig
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*.png
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# Python Virtual Environment
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aerpaw/venv/
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@@ -0,0 +1,3 @@
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[submodule "aerpaw/aerpawlib"]
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path = aerpaw/aerpawlib
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url = https://github.com/morzack/aerpawlib-vehicle-control.git
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+2
-6
@@ -6,8 +6,6 @@ classdef agent
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% State
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lastPos = NaN(1, 3); % position from previous timestep
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pos = NaN(1, 3); % current position
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vel = zeros(1, 3); % velocity (double-integrator mode)
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lastVel = zeros(1, 3); % pre-step velocity (double-integrator mode)
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% Sensor
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sensorModel;
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@@ -32,9 +30,7 @@ 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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@@ -50,8 +46,8 @@ 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, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents);
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[partitioning, agents] = partition(obj, agents, objective)
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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, f] = plot(obj, ind, f);
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updatePlots(obj);
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end
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+3
-9
@@ -1,4 +1,4 @@
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function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, initialMaxAngleStepSize, label, plotCommsGeometry)
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function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, maxIter, initialStepSize, 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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@@ -7,7 +7,6 @@ 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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@@ -16,17 +15,12 @@ function obj = initialize(obj, pos, collisionGeometry, sensorModel, comRange, ma
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end
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obj.pos = pos;
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obj.lastPos = pos;
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obj.vel = zeros(1, 3);
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obj.lastVel = zeros(1, 3);
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obj.collisionGeometry = collisionGeometry;
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obj.sensorModel = sensorModel;
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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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@@ -38,5 +32,5 @@ 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.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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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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end
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+3
-18
@@ -1,4 +1,4 @@
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function [partitioning, agents] = partition(obj, agents, objective)
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function [partitioning] = 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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@@ -6,7 +6,6 @@ function [partitioning, agents] = 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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@@ -19,22 +18,8 @@ function [partitioning, agents] = 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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p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
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[objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
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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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+37
-99
@@ -1,27 +1,16 @@
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function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents)
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function obj = run(obj, domain, partitioning, timestepIndex, index, agents)
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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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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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agents (:, 1) {mustBeA(agents, "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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end
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% Always update lastPos/lastVel so constrainMotion evaluates barriers at
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% the correct (most recent) position, even when this agent has no partition.
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obj.lastPos = obj.pos;
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if useDoubleIntegrator
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obj.lastVel = obj.vel;
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end
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% Collect objective function values across partition
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partitionMask = partitioning == index;
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if ~any(partitionMask(:))
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@@ -34,62 +23,33 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
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maskedX = domain.objective.X(partitionMask);
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maskedY = domain.objective.Y(partitionMask);
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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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% 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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% Apply delta to position
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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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pos = obj.pos + delta * deltaApplicator(ii, 1:3);
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% Compute performance values on partition
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if isa(obj.sensorModel, "sigmoidSensor")
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if ii < 6
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% Compute sensing performance
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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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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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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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% 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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else
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error("?");
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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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end
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% Rearrange data into image arrays
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@@ -103,53 +63,31 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
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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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|
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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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|
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% Compute gradient by finite central differences
|
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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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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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|
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% Compute scaling factor
|
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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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targetRate = obj.initialStepSize - obj.stepDecayRate * timestepIndex; % slow down as you get closer
|
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gradNorm = norm(gradC);
|
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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 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 = (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(1:3) * dt) / (1 + dampingCoeff * dt);
|
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obj.pos = obj.lastPos + obj.vel * dt;
|
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% Compute unconstrained next position.
|
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% Guard against near-zero gradient: when sensor performance is saturated
|
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% or near-zero across the whole partition, rateFactor -> Inf and pNext
|
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% explodes. Stay put instead.
|
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if gradNorm < 1e-100
|
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pNext = obj.pos;
|
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else
|
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% Single-integrator: gradient directly sets position step
|
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if gradPosNorm >= 1e-100
|
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obj.pos = obj.pos + (targetPosRate / gradPosNorm) * gradC(1:3);
|
||||
end
|
||||
pNext = obj.pos + (targetRate / gradNorm) * gradC;
|
||||
end
|
||||
|
||||
% Update tilt and azimuth, saturating at the decaying maximum allowed step size
|
||||
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);
|
||||
obj.sensorModel.azimuth = obj.sensorModel.azimuth + sign(gradC(5)) * min(abs(gradC(5)), maxAngleStep);
|
||||
end
|
||||
% Move to next position
|
||||
obj.lastPos = obj.pos;
|
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obj.pos = pNext;
|
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|
||||
% Reinitialize collision geometry in the new position
|
||||
d = obj.pos - obj.collisionGeometry.center;
|
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|
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+29
-52
@@ -7,68 +7,45 @@ function updatePlots(obj)
|
||||
|
||||
% Find change in agent position since last timestep
|
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deltaPos = obj.pos - obj.lastPos;
|
||||
posChanged = ~(all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3)));
|
||||
orientChanged = obj.sensorModel.tilt ~= obj.fovGeometry.tilt || ...
|
||||
obj.sensorModel.azimuth ~= obj.fovGeometry.azimuth;
|
||||
|
||||
if ~posChanged && ~orientChanged
|
||||
if all(isnan(deltaPos)) || all(deltaPos == zeros(1, 3))
|
||||
% Agent did not move, so nothing has to move on the plots
|
||||
return;
|
||||
end
|
||||
|
||||
if posChanged
|
||||
% Scatterplot point positions
|
||||
for ii = 1:size(obj.scatterPoints, 1)
|
||||
obj.scatterPoints(ii).XData = obj.pos(1);
|
||||
obj.scatterPoints(ii).YData = obj.pos(2);
|
||||
obj.scatterPoints(ii).ZData = obj.pos(3);
|
||||
end
|
||||
% Scatterplot point positions
|
||||
for ii = 1:size(obj.scatterPoints, 1)
|
||||
obj.scatterPoints(ii).XData = obj.pos(1);
|
||||
obj.scatterPoints(ii).YData = obj.pos(2);
|
||||
obj.scatterPoints(ii).ZData = obj.pos(3);
|
||||
end
|
||||
|
||||
% Collision geometry edges
|
||||
for jj = 1:size(obj.collisionGeometry.lines, 2)
|
||||
% Collision geometry edges
|
||||
for jj = 1:size(obj.collisionGeometry.lines, 2)
|
||||
% Update plotting
|
||||
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
|
||||
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
|
||||
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
|
||||
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
|
||||
end
|
||||
end
|
||||
|
||||
% Communications geometry edges
|
||||
if obj.plotCommsGeometry
|
||||
for jj = 1:size(obj.commsGeometry.lines, 2)
|
||||
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
|
||||
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
|
||||
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
|
||||
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
|
||||
end
|
||||
end
|
||||
|
||||
% Communications geometry edges
|
||||
if obj.plotCommsGeometry
|
||||
for jj = 1:size(obj.commsGeometry.lines, 2)
|
||||
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
|
||||
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
|
||||
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
|
||||
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
% FOV cone: recompute full mesh whenever position or orientation changes
|
||||
if ~isempty(obj.fovGeometry.surface)
|
||||
% Sync fovGeometry state to current agent position and sensor orientation
|
||||
obj.fovGeometry = obj.fovGeometry.initialize( ...
|
||||
obj.pos, obj.fovGeometry.radius, obj.fovGeometry.height, ...
|
||||
obj.fovGeometry.tag, obj.fovGeometry.label, ...
|
||||
obj.sensorModel.tilt, obj.sensorModel.azimuth);
|
||||
|
||||
% Recompute cone mesh (mirrors cone.plot logic)
|
||||
maxAlt = obj.fovGeometry.surface(1).Parent.ZLim(2);
|
||||
scalingFactor = maxAlt / obj.fovGeometry.height;
|
||||
[X, Y, Z] = cylinder([scalingFactor * obj.fovGeometry.radius, 0], obj.fovGeometry.n);
|
||||
Z = Z * maxAlt;
|
||||
Ry = [cosd(obj.fovGeometry.tilt), 0, -sind(obj.fovGeometry.tilt); 0, 1, 0; sind(obj.fovGeometry.tilt), 0, cosd(obj.fovGeometry.tilt)];
|
||||
Rz = [sind(obj.fovGeometry.azimuth), -cosd(obj.fovGeometry.azimuth), 0; cosd(obj.fovGeometry.azimuth), sind(obj.fovGeometry.azimuth), 0; 0, 0, 1];
|
||||
R = Rz * Ry;
|
||||
pts = R * [X(:)'; Y(:)'; Z(:)' - maxAlt];
|
||||
X = reshape(pts(1, :), size(X)) + obj.pos(1);
|
||||
Y = reshape(pts(2, :), size(Y)) + obj.pos(2);
|
||||
Z = reshape(pts(3, :) + maxAlt, size(Z)) + obj.pos(3) - maxAlt;
|
||||
|
||||
for jj = 1:size(obj.fovGeometry.surface, 2)
|
||||
obj.fovGeometry.surface(jj).XData = X;
|
||||
obj.fovGeometry.surface(jj).YData = Y;
|
||||
obj.fovGeometry.surface(jj).ZData = Z;
|
||||
end
|
||||
% Update FOV geometry surfaces
|
||||
for jj = 1:size(obj.fovGeometry.surface, 2)
|
||||
% Update each plot
|
||||
% obj.fovGeometry = obj.fovGeometry.plot(obj.spatialPlotIndices)
|
||||
obj.fovGeometry.surface(jj).XData = obj.fovGeometry.surface(jj).XData + deltaPos(1);
|
||||
obj.fovGeometry.surface(jj).YData = obj.fovGeometry.surface(jj).YData + deltaPos(2);
|
||||
obj.fovGeometry.surface(jj).ZData = obj.fovGeometry.surface(jj).ZData + deltaPos(3);
|
||||
end
|
||||
end
|
||||
end
|
||||
+48
-88
@@ -8,41 +8,41 @@ function [obj] = constrainMotion(obj)
|
||||
|
||||
nAgents = size(obj.agents, 1);
|
||||
|
||||
% Compute current velocity and desired control input
|
||||
v = zeros(nAgents, 3); % current velocity (for drift term in DI mode)
|
||||
u_desired = zeros(nAgents, 3); % desired control: velocity (SI) or acceleration (DI)
|
||||
if nAgents < 2
|
||||
nAAPairs = 0;
|
||||
else
|
||||
nAAPairs = nchoosek(nAgents, 2); % unique agent/agent pairs
|
||||
end
|
||||
|
||||
% Compute velocity matrix from unconstrained gradient-ascent step
|
||||
v = zeros(nAgents, 3);
|
||||
for ii = 1:nAgents
|
||||
if obj.useDoubleIntegrator
|
||||
v(ii, :) = obj.agents{ii}.lastVel;
|
||||
u_desired(ii, :) = (obj.agents{ii}.vel - obj.agents{ii}.lastVel) / obj.timestep;
|
||||
else
|
||||
v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
|
||||
u_desired(ii, :) = v(ii, :);
|
||||
end
|
||||
v(ii, :) = (obj.agents{ii}.pos - obj.agents{ii}.lastPos) ./ obj.timestep;
|
||||
end
|
||||
if ~obj.useDoubleIntegrator && (all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all"))
|
||||
% Single-integrator: agents are not attempting to move
|
||||
return;
|
||||
end
|
||||
if obj.useDoubleIntegrator && all(u_desired == 0, "all") && all(v == 0, "all")
|
||||
% Double-integrator: no desired acceleration and no existing velocity
|
||||
if all(isnan(v), "all") || all(v == zeros(nAgents, 3), "all")
|
||||
% Agents are not attempting to move, so there is no motion to be
|
||||
% constrained
|
||||
return;
|
||||
end
|
||||
|
||||
% Initialize QP based on number of agents and obstacles
|
||||
nAOPairs = nAgents * size(obj.obstacles, 1); % unique agent/obstacle pairs
|
||||
nADPairs = nAgents * 6; % agents x (4 walls + 1 floor + 1 ceiling)
|
||||
nLNAPairs = sum(obj.constraintAdjacencyMatrix, "all") - nAgents;
|
||||
total = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
|
||||
kk = 1;
|
||||
A = zeros(obj.numBarriers, 3 * nAgents);
|
||||
b = zeros(obj.numBarriers, 1);
|
||||
A = zeros(total, 3 * nAgents);
|
||||
b = zeros(total, 1);
|
||||
|
||||
% Set up collision avoidance constraints
|
||||
h = NaN(nAgents, nAgents);
|
||||
h(logical(eye(nAgents))) = 0; % self value is 0
|
||||
for ii = 1:(nAgents - 1)
|
||||
for jj = (ii + 1):nAgents
|
||||
h(ii, jj) = norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
|
||||
h(ii, jj) = norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2 - (obj.agents{ii}.collisionGeometry.radius + obj.agents{jj}.collisionGeometry.radius)^2;
|
||||
h(jj, ii) = h(ii, jj);
|
||||
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
|
||||
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
|
||||
% Slack derived from existing params: recovery velocity = max gradient approach velocity.
|
||||
% Correction splits between 2 agents, so |A| = 2*r_sum
|
||||
@@ -60,22 +60,16 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
end
|
||||
|
||||
idx = length(h(triu(true(size(h)), 1)));
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(1:idx, obj.timestepIndex) = h(triu(true(size(h)), 1));
|
||||
end
|
||||
idx = idx + 1;
|
||||
|
||||
hObs = NaN(nAgents, size(obj.obstacles, 1));
|
||||
% Set up obstacle avoidance constraints
|
||||
for ii = 1:nAgents
|
||||
for jj = 1:size(obj.obstacles, 1)
|
||||
% find closest position to agent on/in obstacle
|
||||
cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.lastPos);
|
||||
cPos = obj.obstacles{jj}.closestToPoint(obj.agents{ii}.pos);
|
||||
|
||||
hObs(ii, jj) = dot(obj.agents{ii}.lastPos - cPos, obj.agents{ii}.lastPos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
|
||||
hObs(ii, jj) = dot(obj.agents{ii}.pos - cPos, obj.agents{ii}.pos - cPos) - obj.agents{ii}.collisionGeometry.radius^2;
|
||||
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.lastPos - cPos);
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = -2 * (obj.agents{ii}.pos - cPos);
|
||||
% Floor for single-agent constraint: full correction on one agent, |A| = 2*r_i
|
||||
r_i = obj.agents{ii}.collisionGeometry.radius;
|
||||
v_max_i = obj.agents{ii}.initialStepSize / obj.timestep;
|
||||
@@ -86,56 +80,51 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(idx:(idx + numel(hObs) - 1), obj.timestepIndex) = reshape(hObs, [], 1);
|
||||
end
|
||||
idx = idx + numel(hObs);
|
||||
|
||||
% Set up domain constraints (walls and ceiling only)
|
||||
% Floor constraint is implicit with an obstacle corresponding to the
|
||||
% minimum allowed altitude, but I included it anyways
|
||||
h_xMin = 0.0; h_xMax = 0.0; h_yMin = 0.0; h_yMax = 0.0; h_zMin = 0.0; h_zMax = 0.0;
|
||||
for ii = 1:nAgents
|
||||
% X minimum
|
||||
h_xMin = (obj.agents{ii}.lastPos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_xMin = (obj.agents{ii}.pos(1) - obj.domain.minCorner(1)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [-1, 0, 0];
|
||||
b(kk) = obj.barrierGain * max(0, h_xMin)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
% X maximum
|
||||
h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.lastPos(1)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_xMax = (obj.domain.maxCorner(1) - obj.agents{ii}.pos(1)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [1, 0, 0];
|
||||
b(kk) = obj.barrierGain * max(0, h_xMax)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
% Y minimum
|
||||
h_yMin = (obj.agents{ii}.lastPos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_yMin = (obj.agents{ii}.pos(2) - obj.domain.minCorner(2)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [0, -1, 0];
|
||||
b(kk) = obj.barrierGain * max(0, h_yMin)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
% Y maximum
|
||||
h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.lastPos(2)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_yMax = (obj.domain.maxCorner(2) - obj.agents{ii}.pos(2)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [0, 1, 0];
|
||||
b(kk) = obj.barrierGain * max(0, h_yMax)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
% Z minimum — enforce z >= minAlt + radius (not just z >= domain floor + radius)
|
||||
h_zMin = (obj.agents{ii}.lastPos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_zMin = (obj.agents{ii}.pos(3) - obj.minAlt) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, -1];
|
||||
b(kk) = obj.barrierGain * max(0, h_zMin)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
|
||||
% Z maximum
|
||||
h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.lastPos(3)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
h_zMax = (obj.domain.maxCorner(3) - obj.agents{ii}.pos(3)) - obj.agents{ii}.collisionGeometry.radius;
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = [0, 0, 1];
|
||||
b(kk) = obj.barrierGain * max(0, h_zMax)^obj.barrierExponent;
|
||||
kk = kk + 1;
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(idx:(idx + 5), obj.timestepIndex) = [h_xMin; h_xMax; h_yMin; h_yMax; h_zMin; h_zMax];
|
||||
end
|
||||
idx = idx + 6;
|
||||
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;];
|
||||
end
|
||||
|
||||
% Add communication network constraints
|
||||
@@ -144,44 +133,21 @@ function [obj] = constrainMotion(obj)
|
||||
for ii = 1:(nAgents - 1)
|
||||
for jj = (ii + 1):nAgents
|
||||
if obj.constraintAdjacencyMatrix(ii, jj)
|
||||
paddingFactor = 0.9; % Barrier at 90% of actual range; real comms still work beyond this
|
||||
r_comms = paddingFactor * min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius]);
|
||||
hComms(ii, jj) = r_comms^2 - norm(obj.agents{ii}.lastPos - obj.agents{jj}.lastPos)^2;
|
||||
hComms(ii, jj) = min([obj.agents{ii}.commsGeometry.radius, obj.agents{jj}.commsGeometry.radius])^2 - norm(obj.agents{ii}.pos - obj.agents{jj}.pos)^2;
|
||||
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (obj.agents{ii}.lastPos - obj.agents{jj}.lastPos);
|
||||
A(kk, (3 * ii - 2):(3 * ii)) = 2 * (obj.agents{ii}.pos - obj.agents{jj}.pos);
|
||||
A(kk, (3 * jj - 2):(3 * jj)) = -A(kk, (3 * ii - 2):(3 * ii));
|
||||
|
||||
% One-step forward invariance: b = h/dt ensures h cannot
|
||||
% go negative in a single timestep (linear approximation)
|
||||
v_max_ij = max(obj.agents{ii}.initialStepSize, obj.agents{jj}.initialStepSize) / obj.timestep;
|
||||
hMin = -4 * r_comms * v_max_ij * obj.timestep;
|
||||
if norm(A(kk, :)) < 1e-9
|
||||
b(kk) = 0;
|
||||
else
|
||||
b(kk) = max(hMin, hComms(ii, jj)) / obj.timestep;
|
||||
end
|
||||
b(kk) = obj.barrierGain * max(0, hComms(ii, jj))^obj.barrierExponent;
|
||||
|
||||
kk = kk + 1;
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
if coder.target('MATLAB')
|
||||
obj.barriers(idx:(idx + length(hComms(triu(true(size(hComms)), 1))) - 1), obj.timestepIndex) = hComms(triu(true(size(hComms)), 1));
|
||||
end
|
||||
|
||||
% Double-integrator: transform QP from velocity to acceleration space.
|
||||
% Single-integrator constraint: A * v <= b
|
||||
% Double-integrator: A * a <= (b - A * v_current) / dt
|
||||
if obj.useDoubleIntegrator
|
||||
v_flat = reshape(v', 3 * nAgents, 1);
|
||||
b = (b - A * v_flat) / obj.timestep;
|
||||
end
|
||||
|
||||
% Solve QP: minimize ||u - u_desired||²
|
||||
uhat = reshape(u_desired', 3 * nAgents, 1);
|
||||
% Solve QP program generated earlier
|
||||
vhat = reshape(v', 3 * nAgents, 1);
|
||||
H = 2 * eye(3 * nAgents);
|
||||
f = -2 * uhat;
|
||||
f = -2 * vhat;
|
||||
|
||||
% Update solution based on constraints
|
||||
if coder.target('MATLAB')
|
||||
@@ -191,8 +157,8 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
opt = optimoptions("quadprog", "Display", "off", "Algorithm", "active-set", "UseCodegenSolver", true);
|
||||
x0 = zeros(size(H, 1), 1);
|
||||
[uNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
|
||||
uNew = reshape(uNew, 3, nAgents)';
|
||||
[vNew, ~, exitflag] = quadprog(H, double(f), A, b, [], [], [], [], x0, opt);
|
||||
vNew = reshape(vNew, 3, nAgents)';
|
||||
|
||||
if exitflag < 0
|
||||
% Infeasible or other hard failure: hold all agents at current positions
|
||||
@@ -201,9 +167,9 @@ function [obj] = constrainMotion(obj)
|
||||
else
|
||||
fprintf("[constrainMotion] QP infeasible (exitflag=%d), holding positions\n", int16(exitflag));
|
||||
end
|
||||
uNew = zeros(nAgents, 3);
|
||||
vNew = zeros(nAgents, 3);
|
||||
elseif exitflag == 0
|
||||
% Max iterations exceeded: use suboptimal solution already in uNew
|
||||
% Max iterations exceeded: use suboptimal solution already in vNew
|
||||
if coder.target('MATLAB')
|
||||
warning("QP max iterations exceeded, using suboptimal solution.");
|
||||
else
|
||||
@@ -211,16 +177,10 @@ function [obj] = constrainMotion(obj)
|
||||
end
|
||||
end
|
||||
|
||||
% Update agent state using the constrained control input
|
||||
for ii = 1:size(uNew, 1)
|
||||
if obj.useDoubleIntegrator
|
||||
% uNew is constrained acceleration
|
||||
obj.agents{ii}.vel = obj.agents{ii}.lastVel + uNew(ii, :) * obj.timestep;
|
||||
obj.agents{ii}.pos = obj.agents{ii}.lastPos + obj.agents{ii}.vel * obj.timestep;
|
||||
else
|
||||
% uNew is constrained velocity
|
||||
obj.agents{ii}.pos = obj.agents{ii}.lastPos + uNew(ii, :) * obj.timestep;
|
||||
end
|
||||
% Update the "next position" that was previously set by unconstrained
|
||||
% GA using the constrained solution produced here
|
||||
for ii = 1:size(vNew, 1)
|
||||
obj.agents{ii}.pos = obj.agents{ii}.lastPos + vNew(ii, :) * obj.timestep;
|
||||
end
|
||||
|
||||
% Here we run this at the simulation level, but in reality there is no
|
||||
@@ -228,4 +188,4 @@ function [obj] = constrainMotion(obj)
|
||||
% Running at the simulation level is just meant to simplify the
|
||||
% simulation
|
||||
|
||||
end
|
||||
end
|
||||
+5
-40
@@ -1,4 +1,4 @@
|
||||
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology, optimizeSensorPointing)
|
||||
function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
domain (1, 1) {mustBeGeometry};
|
||||
@@ -11,10 +11,6 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
|
||||
makePlots(1, 1) logical = true;
|
||||
makeVideo (1, 1) logical = true;
|
||||
useDoubleIntegrator (1, 1) logical = false;
|
||||
dampingCoeff (1, 1) double = 2.0;
|
||||
useFixedTopology (1, 1) logical = false;
|
||||
optimizeSensorPointing (1, 1) logical = false;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
@@ -90,19 +86,9 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
obj.barrierExponent = barrierExponent;
|
||||
obj.minAlt = minAlt;
|
||||
|
||||
% Set dynamics model
|
||||
obj.useDoubleIntegrator = useDoubleIntegrator;
|
||||
obj.dampingCoeff = dampingCoeff;
|
||||
obj.useFixedTopology = useFixedTopology;
|
||||
obj.optimizeSensorPointing = optimizeSensorPointing;
|
||||
|
||||
% Compute adjacency matrix and network topology
|
||||
% Compute adjacency matrix and lesser neighbors
|
||||
obj = obj.updateAdjacency();
|
||||
if obj.useFixedTopology
|
||||
obj.constraintAdjacencyMatrix = obj.adjacency;
|
||||
else
|
||||
obj = obj.lesserNeighbor();
|
||||
end
|
||||
obj = obj.lesserNeighbor();
|
||||
|
||||
% Set up times to iterate over
|
||||
obj.times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
|
||||
@@ -111,39 +97,18 @@ function [obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, m
|
||||
% Prepare performance data store (at t = 0, all have 0 performance)
|
||||
obj.perf = [zeros(size(obj.agents, 1) + 1, 1), NaN(size(obj.agents, 1) + 1, size(obj.partitioningTimes, 1) - 1)];
|
||||
|
||||
% Prepare h function data store
|
||||
obj.h = NaN(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2 + size(obj.agents, 1) * size(obj.obstacles, 1) + 6, size(obj.times, 1));
|
||||
end
|
||||
|
||||
% Create initial partitioning
|
||||
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
|
||||
% Determine number of barrier functions that will be necessary
|
||||
if size(obj.agents, 1) < 2
|
||||
nAAPairs = 0;
|
||||
else
|
||||
nAAPairs = nchoosek(size(obj.agents, 1), 2); % unique agent/agent pairs
|
||||
end
|
||||
nAOPairs = size(obj.agents, 1) * size(obj.obstacles, 1); % unique agent/obstacle pairs
|
||||
nADPairs = size(obj.agents, 1) * 6; % agents x (4 walls + 1 floor + 1 ceiling)
|
||||
nLNAPairs = sum(triu(obj.constraintAdjacencyMatrix, 1), "all");
|
||||
obj.numBarriers = nAAPairs + nAOPairs + nADPairs + nLNAPairs;
|
||||
|
||||
if coder.target('MATLAB')
|
||||
% Initialize variable that will store agent positions for trail plots
|
||||
obj.posHist = NaN(size(obj.agents, 1), obj.maxIter + 1, 3);
|
||||
obj.posHist(1:size(obj.agents, 1), 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
|
||||
|
||||
% Initialize velocity history (zeros at t=0, all agents start at rest)
|
||||
obj.velHist = zeros(size(obj.agents, 1), obj.maxIter + 1, 3);
|
||||
|
||||
% Initialize variable that will store barrier function values per timestep for analysis purposes
|
||||
obj.barriers = NaN(obj.numBarriers, size(obj.times, 1));
|
||||
|
||||
% Initialize constraint adjacency history (nAgents x nAgents x nTimesteps)
|
||||
nAgents = size(obj.agents, 1);
|
||||
obj.constraintAdjacencyHist = false(nAgents, nAgents, size(obj.times, 1));
|
||||
obj.constraintAdjacencyHist(:, :, 1) = obj.constraintAdjacencyMatrix;
|
||||
|
||||
|
||||
% Set up plots showing initialized state
|
||||
obj = obj.plot();
|
||||
|
||||
|
||||
@@ -52,19 +52,8 @@ BETA_TILT_VEC = scenario.betaTilt; % 1×N
|
||||
|
||||
DOMAIN_MIN = scenario.domainMin; % 1×3
|
||||
DOMAIN_MAX = scenario.domainMax; % 1×3
|
||||
|
||||
% objectivePos: 2 values per Gaussian component (1 or 2 components supported)
|
||||
nObjComponents = numel(scenario.objectivePos) / 2;
|
||||
assert(mod(numel(scenario.objectivePos), 2) == 0, ...
|
||||
'objectivePos must have an even number of values (2 per Gaussian component)');
|
||||
assert(nObjComponents >= 1 && nObjComponents <= 2, ...
|
||||
'At most 2 objective Gaussian components supported; got %d', nObjComponents);
|
||||
assert(numel(scenario.objectiveVar) == nObjComponents * 4, ...
|
||||
'objectiveVar must have %d values for %d component(s); got %d', ...
|
||||
nObjComponents * 4, nObjComponents, numel(scenario.objectiveVar));
|
||||
OBJECTIVE_GROUND_POS = reshape(scenario.objectivePos, 2, nObjComponents)'; % nObj×2
|
||||
OBJECTIVE_VAR = permute(reshape(scenario.objectiveVar, 2, 2, nObjComponents), [3, 1, 2]); % nObj×2×2
|
||||
|
||||
OBJECTIVE_GROUND_POS = scenario.objectivePos; % 1×2
|
||||
OBJECTIVE_VAR = reshape(scenario.objectiveVar, 2, 2); % 2×2 covariance matrix
|
||||
SENSOR_PERFORMANCE_MINIMUM = scenario.sensorPerformanceMinimum; % scalar
|
||||
|
||||
% Initial UAV positions: flat vector reshaped to N×3
|
||||
@@ -90,23 +79,6 @@ assert(numel(BETA_TILT_VEC) == numAgents, ...
|
||||
|
||||
numObstacles = scenario.numObstacles;
|
||||
|
||||
% Dynamics model (optional columns — backward compatible with older CSVs)
|
||||
if isfield(scenario, 'useDoubleIntegrator')
|
||||
USE_DOUBLE_INTEGRATOR = logical(scenario.useDoubleIntegrator);
|
||||
else
|
||||
USE_DOUBLE_INTEGRATOR = false;
|
||||
end
|
||||
if isfield(scenario, 'dampingCoeff')
|
||||
DAMPING_COEFF = scenario.dampingCoeff;
|
||||
else
|
||||
DAMPING_COEFF = 2.0;
|
||||
end
|
||||
if isfield(scenario, 'useFixedTopology')
|
||||
USE_FIXED_TOPOLOGY = logical(scenario.useFixedTopology);
|
||||
else
|
||||
USE_FIXED_TOPOLOGY = false;
|
||||
end
|
||||
|
||||
% ---- Build domain --------------------------------------------------------
|
||||
dom = rectangularPrism;
|
||||
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
|
||||
@@ -152,7 +124,6 @@ end
|
||||
|
||||
% ---- Initialise simulation (plots and video disabled) --------------------
|
||||
obj = obj.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
|
||||
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false, ...
|
||||
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
|
||||
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
|
||||
|
||||
end
|
||||
|
||||
@@ -1,87 +0,0 @@
|
||||
function obj = initializeFromInits(obj, initsPath)
|
||||
% INITIALIZEFROMINITS Initialize miSim from a saved simInits matfile.
|
||||
%
|
||||
% Loads all simulation parameters and initial agent states written by
|
||||
% writeInits(), reconstructs domain, objective, agents, and obstacles, then
|
||||
% calls the standard obj.initialize() method. Plots and video are disabled.
|
||||
%
|
||||
% Usage:
|
||||
% sim = sim.initializeFromInits('sandbox/2025_01_01_12_00_00_miSimInits.mat');
|
||||
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
initsPath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
end
|
||||
|
||||
inits = load(initsPath);
|
||||
|
||||
% ---- Build domain ------------------------------------------------------------
|
||||
dom = rectangularPrism;
|
||||
dom = dom.initialize([inits.domainMin; inits.domainMax], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% ---- Build sensing objective -------------------------------------------------
|
||||
dom.objective = sensingObjective;
|
||||
% reshape guards against MATLAB flattening the 1×2×2 singleton dimension on load
|
||||
objSigma = reshape(inits.objectiveSigma, [1 2 2]);
|
||||
objFcn = objectiveFunctionWrapper(inits.objectivePos, objSigma);
|
||||
dom.objective = dom.objective.initialize(objFcn, dom, ...
|
||||
inits.discretizationStep, inits.protectedRange, inits.sensorPerformanceMinimum, ...
|
||||
inits.objectivePos, objSigma);
|
||||
|
||||
% ---- Build agents ------------------------------------------------------------
|
||||
numAgents = inits.numAgents;
|
||||
agentList = cell(numAgents, 1);
|
||||
for ii = 1:numAgents
|
||||
pos = inits.pos(ii, :);
|
||||
|
||||
sensor = sigmoidSensor;
|
||||
sensor = sensor.initialize(inits.alphaDist(ii), inits.betaDist(ii), ...
|
||||
inits.alphaTilt(ii), inits.betaTilt(ii));
|
||||
|
||||
geom = spherical;
|
||||
geom = geom.initialize(pos, inits.collisionRadius(ii), REGION_TYPE.COLLISION, ...
|
||||
sprintf("UAV %d Collision", ii));
|
||||
ag = agent;
|
||||
ag = ag.initialize(pos, geom, sensor, inits.comRange(ii), inits.maxIter, ...
|
||||
inits.initialStepSize(ii), sprintf("UAV %d", ii));
|
||||
agentList{ii} = ag;
|
||||
end
|
||||
|
||||
% ---- Build obstacles ---------------------------------------------------------
|
||||
numObstacles = inits.numObstacles;
|
||||
obstacleList = cell(numObstacles, 1);
|
||||
if numObstacles > 0
|
||||
for ii = 1:numObstacles
|
||||
obs = rectangularPrism;
|
||||
obs = obs.initialize([inits.obsMinCorners(ii, :); inits.obsMaxCorners(ii, :)], ...
|
||||
REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii));
|
||||
obstacleList{ii} = obs;
|
||||
end
|
||||
end
|
||||
|
||||
% ---- Optional backward-compat fields -----------------------------------------
|
||||
if isfield(inits, 'useDoubleIntegrator')
|
||||
useDoubleIntegrator = logical(inits.useDoubleIntegrator);
|
||||
else
|
||||
useDoubleIntegrator = false;
|
||||
end
|
||||
if isfield(inits, 'dampingCoeff')
|
||||
dampingCoeff = inits.dampingCoeff;
|
||||
else
|
||||
dampingCoeff = 2.0;
|
||||
end
|
||||
if isfield(inits, 'useFixedTopology')
|
||||
useFixedTopology = logical(inits.useFixedTopology);
|
||||
else
|
||||
useFixedTopology = false;
|
||||
end
|
||||
|
||||
% ---- Initialize simulation (plots and video disabled) ------------------------
|
||||
obj = obj.initialize(dom, agentList, inits.barrierGain, inits.barrierExponent, ...
|
||||
inits.minAlt, inits.timestep, inits.maxIter, obstacleList, ...
|
||||
false, false, useDoubleIntegrator, dampingCoeff, useFixedTopology);
|
||||
|
||||
end
|
||||
+4
-11
@@ -7,6 +7,7 @@ classdef miSim
|
||||
timestepIndex = NaN; % index of the current timestep (useful for time-indexed arrays)
|
||||
maxIter = NaN; % maximum number of simulation iterations
|
||||
domain;
|
||||
objective;
|
||||
obstacles; % geometries that define obstacles within the domain
|
||||
agents; % agents that move within the domain
|
||||
adjacency = false(0, 0); % Adjacency matrix representing communications network graph
|
||||
@@ -17,18 +18,11 @@ classdef miSim
|
||||
barrierGain = NaN; % CBF gain parameter
|
||||
barrierExponent = NaN; % CBF exponent parameter
|
||||
minAlt = 0; % minimum allowable altitude (m)
|
||||
useDoubleIntegrator = false; % false = single-integrator, true = double-integrator dynamics
|
||||
dampingCoeff = 2.0; % velocity-proportional damping for double-integrator mode
|
||||
useFixedTopology = false; % false = lesser neighbor (dynamic), true = fixed initial topology
|
||||
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
|
||||
% Indicies for various plot types in the main tiled layout figure
|
||||
spatialPlotIndices = [6, 4, 3, 2];
|
||||
numBarriers = 0; % Number of barrier functions needed
|
||||
barriers = []; % log barrier function values at each timestep for analysis
|
||||
constraintAdjacencyHist = []; % log constraint adjacency matrix at each timestep
|
||||
end
|
||||
|
||||
properties (Access = private)
|
||||
@@ -46,7 +40,6 @@ classdef miSim
|
||||
performancePlot; % objects for sensor performance plot
|
||||
|
||||
posHist; % data for trail plot
|
||||
velHist; % velocity history (double-integrator mode)
|
||||
trailPlot; % objects for agent trail plot
|
||||
|
||||
% Indicies for various plot types in the main tiled layout figure
|
||||
@@ -55,6 +48,7 @@ classdef miSim
|
||||
partitionGraphIndex = 1;
|
||||
|
||||
% CBF plotting
|
||||
h; % h function values
|
||||
hf; % h function plotting figure
|
||||
caPlot; % objects for collision avoidance h function plot
|
||||
obsPlot; % objects for obstacle h function plot
|
||||
@@ -67,13 +61,12 @@ classdef miSim
|
||||
obj (1, 1) miSim
|
||||
end
|
||||
obj.domain = rectangularPrism;
|
||||
obj.objective = sensingObjective;
|
||||
obj.obstacles = {rectangularPrism};
|
||||
obj.agents = {agent};
|
||||
end
|
||||
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo, useDoubleIntegrator, dampingCoeff, useFixedTopology);
|
||||
[obj] = initialize(obj, domain, agents, barrierGain, barrierExponent, minAlt, timestep, maxIter, obstacles, makePlots, makeVideo);
|
||||
[obj] = initializeFromCsv(obj, csvPath);
|
||||
[obj] = initializeFromInits(obj, initsPath);
|
||||
[obj] = plotFromSimHist(obj, initsPath, histPath);
|
||||
[obj] = run(obj);
|
||||
[obj] = lesserNeighbor(obj);
|
||||
[obj] = constrainMotion(obj);
|
||||
|
||||
@@ -1,93 +0,0 @@
|
||||
function obj = plotFromSimHist(obj, initsPath, histPath)
|
||||
% PLOTFROMSIMHIST Reconstruct all three miSim plots from saved matfiles.
|
||||
%
|
||||
% Loads the simInits matfile to rebuild domain/obstacle/objective/agent
|
||||
% geometry, then loads the simHist matfile to restore the full time-history
|
||||
% arrays. Produces the same three figures that a live run would generate:
|
||||
% 1. Sensor performance vs. time (obj.fPerf)
|
||||
% 2. Barrier function values vs. time (obj.hf)
|
||||
% 3. 3-D spatial figure with domain, obstacles, objective, agent trails,
|
||||
% and final-timestep communications topology (obj.f)
|
||||
%
|
||||
% Usage:
|
||||
% sim = miSim;
|
||||
% sim = sim.plotFromSimHist( ...
|
||||
% 'sandbox/2025_01_01_12_00_00_miSimHist.mat', ...
|
||||
% 'sandbox/2025_01_01_12_00_00_miSimInits.mat');
|
||||
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
initsPath (1, 1) string;
|
||||
histPath (1, 1) string;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
end
|
||||
|
||||
% ---- Reconstruct geometry from inits (plots disabled) --------------------
|
||||
obj = obj.initializeFromInits(initsPath);
|
||||
nAgents = size(obj.agents, 1);
|
||||
|
||||
% ---- Load history data ---------------------------------------------------
|
||||
data = load(histPath);
|
||||
out = data.out;
|
||||
|
||||
nHistTimesteps = size(out.barriers, 2);
|
||||
nPosTimesteps = size(out.agent(1).pos, 1);
|
||||
|
||||
% ---- Populate barrier history --------------------------------------------
|
||||
% out.barriers may be narrower than the pre-allocated obj.barriers if the
|
||||
% run was shorter than maxIter; fill what we have and leave the rest NaN.
|
||||
obj.barriers(:, 1:nHistTimesteps) = out.barriers;
|
||||
|
||||
% ---- Populate position history and advance agents to final positions -----
|
||||
for ii = 1:nAgents
|
||||
agentPos = out.agent(ii).pos; % (nPosTimesteps × 3)
|
||||
nPts = size(agentPos, 1);
|
||||
obj.posHist(ii, 1:nPts, :) = reshape(agentPos, [1, nPts, 3]);
|
||||
obj.agents{ii}.pos = agentPos(end, :); % show final position in spatial plot
|
||||
end
|
||||
|
||||
% ---- Set final constraint topology ---------------------------------------
|
||||
obj.constraintAdjacencyMatrix = out.constraintAdjacency(:, :, end);
|
||||
|
||||
% ---- Recompute partitioning at final agent positions ---------------------
|
||||
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
|
||||
% ---- Enable plotting and produce spatial + barrier figures ---------------
|
||||
obj.makePlots = true;
|
||||
obj = obj.plot();
|
||||
|
||||
% ---- Performance figure (built directly — live machinery is incremental) -
|
||||
nPerfTimesteps = numel(out.perf);
|
||||
times = (0:nPerfTimesteps - 1) * obj.timestep;
|
||||
normFactor = 1 / max(out.perf);
|
||||
|
||||
obj.fPerf = figure;
|
||||
ax = axes(obj.fPerf);
|
||||
hold(ax, "on");
|
||||
title(ax, "Sensor Performance");
|
||||
xlabel(ax, "Time (s)");
|
||||
ylabel(ax, "Sensor Performance");
|
||||
grid(ax, "on");
|
||||
|
||||
legendStrings = strings(nAgents + 1, 1);
|
||||
legendStrings(1) = "Total";
|
||||
plot(ax, times, out.perf * normFactor, "LineWidth", 1.5);
|
||||
for ii = 1:nAgents
|
||||
agentPerf = out.agent(ii).perf;
|
||||
agentTimes = times(1:numel(agentPerf));
|
||||
plot(ax, agentTimes, agentPerf * normFactor);
|
||||
if isfield(out.agent(ii), 'label')
|
||||
legendStrings(ii + 1) = string(out.agent(ii).label);
|
||||
else
|
||||
legendStrings(ii + 1) = sprintf("Agent %d", ii);
|
||||
end
|
||||
end
|
||||
legend(ax, legendStrings, "Location", "northwest");
|
||||
hold(ax, "off");
|
||||
|
||||
% Bring spatial figure to the front
|
||||
figure(obj.f);
|
||||
|
||||
end
|
||||
+4
-13
@@ -6,10 +6,6 @@ function obj = plotH(obj)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
end
|
||||
|
||||
nCA = size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2;
|
||||
nObs = size(obj.agents, 1) * size(obj.obstacles, 1);
|
||||
nDom = size(obj.agents, 1) * 6;
|
||||
|
||||
obj.hf = figure;
|
||||
tiledlayout(obj.hf, 4, 1, "TileSpacing", "tight", "Padding", "compact");
|
||||
|
||||
@@ -19,7 +15,7 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Collision Avoidance");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.caPlot = plot(obj.barriers(1:nCA, :)');
|
||||
obj.caPlot = plot(obj.h(1:(size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2), :)');
|
||||
legendStrings = [];
|
||||
for ii = 2:size(obj.agents, 1)
|
||||
for jj = 1:(ii - 1)
|
||||
@@ -35,7 +31,7 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Obstacles");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.obsPlot = plot(obj.barriers((nCA + 1):(nCA + nObs), :)');
|
||||
obj.obsPlot = plot(obj.h((1 + (size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)):(((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1)), :)');
|
||||
legendStrings = [];
|
||||
for ii = 1:size(obj.obstacles, 1)
|
||||
for jj = 1:size(obj.agents, 1)
|
||||
@@ -51,13 +47,8 @@ function obj = plotH(obj)
|
||||
xlabel(obj.hf.Children(1).Children(1), "Time (s)");
|
||||
title(obj.hf.Children(1).Children(1), "Domain");
|
||||
hold(obj.hf.Children(1).Children(1), "on");
|
||||
obj.domPlot = plot(obj.barriers((nCA + nObs + 1):(nCA + nObs + nDom), :)');
|
||||
domLabels = ["X Min", "X Max", "Y Min", "Y Max", "Z Min", "Z Max"];
|
||||
legendStrings = strings(nDom, 1);
|
||||
for ii = 1:size(obj.agents, 1)
|
||||
legendStrings((ii - 1) * 6 + (1:6)) = sprintf("A%d ", ii) + domLabels;
|
||||
end
|
||||
legend(obj.hf.Children(1).Children(1), legendStrings, "Location", "bestoutside");
|
||||
obj.domPlot = plot(obj.h((1 + (((size(obj.agents, 1) * (size(obj.agents, 1) - 1) / 2)) + size(obj.agents, 1) * size(obj.obstacles, 1))):size(obj.h, 1), 1:end)');
|
||||
legend(obj.hf.Children(1).Children(1), ["X Min"; "X Max"; "Y Min"; "Y Max"; "Z Min"; "Z Max";], "Location", "bestoutside");
|
||||
hold(obj.hf.Children(1).Children(2), "off");
|
||||
|
||||
nexttile(obj.hf.Children(1));
|
||||
|
||||
+4
-30
@@ -10,13 +10,7 @@ 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
|
||||
|
||||
@@ -31,31 +25,17 @@ 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] = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
obj.partitioning = obj.agents{1}.partition(obj.agents, obj.domain.objective);
|
||||
|
||||
% Determine desired communications links
|
||||
if ~obj.useFixedTopology
|
||||
obj = obj.lesserNeighbor();
|
||||
end
|
||||
|
||||
% Log constraint adjacency for this timestep
|
||||
if coder.target('MATLAB')
|
||||
obj.constraintAdjacencyHist(:, :, ii) = obj.constraintAdjacencyMatrix;
|
||||
end
|
||||
obj = obj.lesserNeighbor();
|
||||
|
||||
% 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.useDoubleIntegrator, obj.dampingCoeff, obj.timestep, obj.optimizeSensorPointing, obj.agents([1:(jj - 1), (jj + 1):size(obj.agents, 1)]));
|
||||
obj.agents{jj} = obj.agents{jj}.run(obj.domain, obj.partitioning, obj.timestepIndex, jj, obj.agents);
|
||||
end
|
||||
|
||||
% Adjust motion determined by unconstrained gradient ascent using
|
||||
@@ -63,9 +43,8 @@ function [obj] = run(obj)
|
||||
obj = constrainMotion(obj);
|
||||
|
||||
if coder.target('MATLAB')
|
||||
% Update agent position and velocity history arrays
|
||||
% Update agent position history array
|
||||
obj.posHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.pos, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
|
||||
obj.velHist(1:size(obj.agents, 1), obj.timestepIndex + 1, 1:3) = reshape(cell2mat(cellfun(@(x) x.vel, obj.agents, "UniformOutput", false)), size(obj.agents, 1), 1, 3);
|
||||
|
||||
% Update total performance
|
||||
obj.performance = [obj.performance, sum(cellfun(@(x) x.performance(obj.timestepIndex+1), obj.agents))];
|
||||
@@ -79,20 +58,15 @@ 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
|
||||
end
|
||||
|
||||
% Close video
|
||||
if coder.target('MATLAB')
|
||||
if obj.makeVideo
|
||||
% Close video file
|
||||
v.close();
|
||||
end
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
+5
-32
@@ -6,52 +6,25 @@ function obj = teardown(obj)
|
||||
obj (1, 1) {mustBeA(obj, "miSim")};
|
||||
end
|
||||
|
||||
% % Close plots
|
||||
% close(obj.hf);
|
||||
% close(obj.fPerf);
|
||||
% close(obj.f);
|
||||
|
||||
% Log results into matfile
|
||||
histPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", strcat(obj.artifactName, "_miSimHist.mat"));
|
||||
out = struct("agent", repmat(struct("pos", [], "vel", [], "perf", [], "sensor", struct("alphaDist", [], "betaDist", [], "alphaTilt", [], "betaTilt", []), "collisionRadius", [], "commsRadius", []), size(obj.agents)), "perf", [], "barriers", [], "useDoubleIntegrator", [], "dampingCoeff", [], "useFixedTopology", []);
|
||||
|
||||
out.perf = obj.performance(1:(end - 1));
|
||||
out.barriers = [zeros(size(obj.barriers(1:end, 1), 1), 1), obj.barriers(1:end, 1:(end - 1))];
|
||||
out.dampingCoeff = obj.dampingCoeff;
|
||||
out.useDoubleIntegrator = obj.useDoubleIntegrator;
|
||||
out.useFixedTopology = obj.useFixedTopology;
|
||||
out.constraintAdjacency = obj.constraintAdjacencyHist(:, :, 1:(end - 1));
|
||||
for ii = 1:size(obj.agents, 1)
|
||||
out.agent(ii).pos = squeeze(obj.posHist(ii, 1:(end - 1), 1:3));
|
||||
out.agent(ii).vel = squeeze(obj.velHist(ii, 1:(end - 1), 1:3));
|
||||
out.agent(ii).perf = obj.agents{ii}.performance(1:(end - 2));
|
||||
out.agent(ii).sensor.alphaDist = obj.agents{ii}.sensorModel.alphaDist;
|
||||
out.agent(ii).sensor.betaDist = obj.agents{ii}.sensorModel.betaDist;
|
||||
out.agent(ii).sensor.alphaTilt = obj.agents{ii}.sensorModel.alphaTilt;
|
||||
out.agent(ii).sensor.betaTilt = obj.agents{ii}.sensorModel.betaTilt;
|
||||
out.agent(ii).collisionRadius = obj.agents{ii}.collisionGeometry.radius;
|
||||
out.agent(ii).commsRadius = obj.agents{ii}.commsGeometry.radius;
|
||||
end
|
||||
|
||||
save(histPath, "out");
|
||||
% Close plots
|
||||
close(obj.hf);
|
||||
close(obj.fPerf);
|
||||
close(obj.f);
|
||||
|
||||
% reset parameters
|
||||
obj.timestep = NaN;
|
||||
obj.timestepIndex = NaN;
|
||||
obj.maxIter = NaN;
|
||||
obj.domain = rectangularPrism;
|
||||
obj.objective = sensingObjective;
|
||||
obj.obstacles = cell(0, 1);
|
||||
obj.agents = cell(0, 1);
|
||||
obj.adjacency = NaN;
|
||||
obj.constraintAdjacencyMatrix = NaN;
|
||||
obj.constraintAdjacencyHist = [];
|
||||
obj.partitioning = NaN;
|
||||
obj.performance = 0;
|
||||
obj.barrierGain = NaN;
|
||||
obj.barrierExponent = NaN;
|
||||
obj.useDoubleIntegrator = false;
|
||||
obj.dampingCoeff = 2.0;
|
||||
obj.useFixedTopology = false;
|
||||
obj.artifactName = "";
|
||||
|
||||
end
|
||||
@@ -61,15 +61,13 @@ function [obj] = updatePlots(obj)
|
||||
end
|
||||
|
||||
% Update h function plots
|
||||
nCA = size(obj.caPlot, 1);
|
||||
nObs = size(obj.obsPlot, 1);
|
||||
for ii = 1:nCA
|
||||
obj.caPlot(ii).YData(obj.timestepIndex) = obj.barriers(ii, obj.timestepIndex);
|
||||
for ii = 1:size(obj.caPlot, 1)
|
||||
obj.caPlot(ii).YData(obj.timestepIndex) = obj.h(ii, obj.timestepIndex);
|
||||
end
|
||||
for ii = 1:nObs
|
||||
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + ii, obj.timestepIndex);
|
||||
for ii = 1:size(obj.obsPlot, 1)
|
||||
obj.obsPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1), obj.timestepIndex);
|
||||
end
|
||||
for ii = 1:size(obj.domPlot, 1)
|
||||
obj.domPlot(ii).YData(obj.timestepIndex) = obj.barriers(nCA + nObs + ii, obj.timestepIndex);
|
||||
obj.domPlot(ii).YData(obj.timestepIndex) = obj.h(ii + size(obj.caPlot, 1) + size(obj.obsPlot, 1), obj.timestepIndex);
|
||||
end
|
||||
end
|
||||
+5
-4
@@ -7,11 +7,11 @@ function validate(obj)
|
||||
|
||||
%% Communications Network Validators
|
||||
if max(conncomp(graph(obj.adjacency))) ~= 1
|
||||
error("Network is not connected");
|
||||
warning("Network is not connected");
|
||||
end
|
||||
|
||||
if any(obj.adjacency - obj.constraintAdjacencyMatrix < 0, "all")
|
||||
error("Eliminated network connections that were necessary");
|
||||
warning("Eliminated network connections that were necessary");
|
||||
end
|
||||
|
||||
%% Obstacle Validators
|
||||
@@ -20,9 +20,10 @@ function validate(obj)
|
||||
for kk = 1:size(obj.agents, 1)
|
||||
P = min(max(obj.agents{kk}.pos, obj.obstacles{jj}.minCorner), obj.obstacles{jj}.maxCorner);
|
||||
d = obj.agents{kk}.pos - P;
|
||||
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2 - 1e-3
|
||||
error("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, - dot(d, d) + obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
|
||||
if dot(d, d) < obj.agents{kk}.collisionGeometry.radius^2
|
||||
warning("%s colliding with %s by %d", obj.agents{kk}.label, obj.obstacles{jj}.label, dot(d, d) - obj.agents{kk}.collisionGeometry.radius^2); % this will cause quadprog to fail
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
end
|
||||
|
||||
+11
-53
@@ -5,71 +5,29 @@ 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.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);
|
||||
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);
|
||||
comRanges = cellfun(@(x) x.commsGeometry.radius, obj.agents);
|
||||
initialStepSize = cellfun(@(x) x.initialStepSize, obj.agents);
|
||||
pos = cell2mat(cellfun(@(x) x.pos, obj.agents, 'UniformOutput', false));
|
||||
obsMinCorners = cell2mat(cellfun(@(x) x.minCorner, userObstacles, 'UniformOutput', false));
|
||||
obsMaxCorners = cell2mat(cellfun(@(x) x.maxCorner, userObstacles, 'UniformOutput', false));
|
||||
|
||||
|
||||
% Combine with simulation parameters
|
||||
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter + 1, "minAlt", obj.minAlt, ...
|
||||
inits = struct("timestep", obj.timestep, "maxIter", obj.maxIter, "minAlt", obj.obstacles{end}.maxCorner(3), ...
|
||||
"discretizationStep", obj.domain.objective.discretizationStep, "protectedRange", obj.domain.objective.protectedRange, ...
|
||||
"sensorPerformanceMinimum", obj.domain.objective.sensorPerformanceMinimum, "initialStepSize", initialStepSize, ...
|
||||
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", numInputObs, ...
|
||||
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, ...
|
||||
"useDoubleIntegrator", obj.useDoubleIntegrator, "dampingCoeff", obj.dampingCoeff, "useFixedTopology", obj.useFixedTopology, ...
|
||||
"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
|
||||
"barrierGain", obj.barrierGain, "barrierExponent", obj.barrierExponent, "numObstacles", size(obj.obstacles, 1), ...
|
||||
"numAgents", size(obj.agents, 1), "collisionRadius", collisionRadii, "comRange", comRanges, "alphaDist", alphaDist, ...
|
||||
"betaDist", betaDist, "alphaTilt", alphaTilt, "betaTilt", betaTilt, ...
|
||||
... % ^^^ PARAMETERS ^^^ | vvv STATES vvv
|
||||
"pos", pos, "objectivePos", obj.domain.objective.groundPos, "objectiveSigma", obj.domain.objective.objectiveSigma, ...
|
||||
"domainMin", obj.domain.minCorner, "domainMax", obj.domain.maxCorner, ...
|
||||
"obsMinCorners", obsMinCorners, "obsMaxCorners", obsMaxCorners, ...
|
||||
"objectiveIntegral", sum(obj.domain.objective.values(:)));
|
||||
"pos", pos);
|
||||
|
||||
% Save all parameters to output file
|
||||
initsFile = strcat(obj.artifactName, "_miSimInits");
|
||||
initsFile = fullfile(matlab.project.rootProject().RootFolder, "sandbox", initsFile);
|
||||
save(initsFile, "-struct", "inits");
|
||||
end
|
||||
end
|
||||
@@ -1,24 +0,0 @@
|
||||
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
|
||||
@@ -1,11 +0,0 @@
|
||||
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
|
||||
@@ -1,6 +0,0 @@
|
||||
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
|
||||
@@ -1,23 +0,0 @@
|
||||
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
|
||||
@@ -1,32 +0,0 @@
|
||||
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
|
||||
@@ -1,13 +0,0 @@
|
||||
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
|
||||
@@ -1,125 +0,0 @@
|
||||
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
|
||||
@@ -1,52 +0,0 @@
|
||||
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
|
||||
@@ -1,91 +0,0 @@
|
||||
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
|
||||
@@ -1,40 +0,0 @@
|
||||
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
|
||||
@@ -1,34 +0,0 @@
|
||||
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
|
||||
@@ -1,23 +0,0 @@
|
||||
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
|
||||
@@ -1,4 +1,4 @@
|
||||
function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum, objectiveMu, objectiveSigma)
|
||||
function obj = initialize(obj, objectiveFunction, domain, discretizationStep, protectedRange, sensorPerformanceMinimum)
|
||||
arguments (Input)
|
||||
obj (1,1) {mustBeA(obj, "sensingObjective")};
|
||||
objectiveFunction (1, 1) {mustBeA(objectiveFunction, "function_handle")};
|
||||
@@ -6,8 +6,6 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
|
||||
discretizationStep (1, 1) double = 1;
|
||||
protectedRange (1, 1) double = 1;
|
||||
sensorPerformanceMinimum (1, 1) double = 1e-6;
|
||||
objectiveMu (:, 2) double = NaN(1, 2);
|
||||
objectiveSigma (:, 2, 2) double = NaN(1, 2, 2);
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1,1) {mustBeA(obj, "sensingObjective")};
|
||||
@@ -38,14 +36,9 @@ function obj = initialize(obj, objectiveFunction, domain, discretizationStep, pr
|
||||
obj.values = obj.values ./ max(obj.values, [], "all");
|
||||
|
||||
% store ground position
|
||||
idx = obj.values == 1;
|
||||
if any(isnan(objectiveMu))
|
||||
obj.groundPos = [obj.X(idx), obj.Y(idx)];
|
||||
obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
|
||||
else
|
||||
obj.groundPos = objectiveMu;
|
||||
end
|
||||
obj.objectiveSigma = objectiveSigma;
|
||||
idx = obj.values == 1;
|
||||
obj.groundPos = [obj.X(idx), obj.Y(idx)];
|
||||
obj.groundPos = obj.groundPos(1, 1:2); % for safety, in case 2 points are maximal (somehow)
|
||||
|
||||
assert(domain.distance([obj.groundPos, ones(size(obj.groundPos, 1), 1) .* domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective");
|
||||
assert(domain.distance([obj.groundPos, domain.center(3)]) > protectedRange, "Domain is crowding the sensing objective")
|
||||
end
|
||||
@@ -11,16 +11,16 @@ function obj = initializeRandomMvnpdf(obj, domain, discretizationStep, protected
|
||||
|
||||
% Set random objective position
|
||||
mu = domain.minCorner;
|
||||
while domain.distance(mu) < protectedRange * 1.01
|
||||
while domain.distance(mu) < protectedRange
|
||||
mu = domain.random();
|
||||
end
|
||||
|
||||
% Set random distribution parameters
|
||||
sig = reshape([2 + rand * 2, 1; 1, 2 + rand * 2], [1 2 2]);
|
||||
sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
|
||||
|
||||
% Set up random bivariate normal distribution function
|
||||
objectiveFunction = objectiveFunctionWrapper(mu(1:2), sig);
|
||||
|
||||
% Regular initialization
|
||||
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange, 1e-6, mu(1:2), sig);
|
||||
obj = obj.initialize(objectiveFunction, domain, discretizationStep, protectedRange);
|
||||
end
|
||||
@@ -11,26 +11,19 @@ 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)
|
||||
ax = f.CurrentAxes;
|
||||
hold(ax, "on");
|
||||
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
|
||||
hold(f.CurrentAxes, "on");
|
||||
o = surf(f.CurrentAxes, obj.X, obj.Y, zeros(size(obj.X)), obj.values ./ max(obj.values, [], "all"), "EdgeColor", "none");
|
||||
o.HitTest = "off";
|
||||
o.PickableParts = "none";
|
||||
clim(ax, cRange);
|
||||
hold(ax, "off");
|
||||
hold(f.CurrentAxes, "off");
|
||||
else
|
||||
ax = f.Children(1).Children(ind(1));
|
||||
hold(ax, "on");
|
||||
o = surf(ax, obj.X, obj.Y, zeros(size(obj.X)), normalized, "EdgeColor", "none");
|
||||
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");
|
||||
o.HitTest = "off";
|
||||
o.PickableParts = "none";
|
||||
clim(ax, cRange);
|
||||
hold(ax, "off");
|
||||
hold(f.Children(1).Children(ind(1)), "off");
|
||||
end
|
||||
|
||||
% Add to other perspectives
|
||||
|
||||
@@ -2,8 +2,7 @@ classdef sensingObjective
|
||||
% Sensing objective definition parent class
|
||||
properties (SetAccess = private, GetAccess = public)
|
||||
label = "";
|
||||
groundPos = NaN(1, 2);
|
||||
objectiveSigma = NaN(1, 2, 2);
|
||||
groundPos = [NaN, NaN];
|
||||
discretizationStep = NaN;
|
||||
X = [];
|
||||
Y = [];
|
||||
|
||||
@@ -1,9 +0,0 @@
|
||||
function value = halfAngle(obj)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "sigmoidSensor")};
|
||||
end
|
||||
arguments (Output)
|
||||
value (1, 1) double;
|
||||
end
|
||||
value = obj.alphaTilt;
|
||||
end
|
||||
@@ -1,24 +1,17 @@
|
||||
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt, tilt, azimuth)
|
||||
function obj = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt)
|
||||
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
|
||||
@@ -8,20 +8,16 @@ function value = sensorPerformance(obj, agentPos, targetPos)
|
||||
value (:, 1) double;
|
||||
end
|
||||
|
||||
% Unit vectors from agent to each target
|
||||
diffs = targetPos - agentPos;
|
||||
d = vecnorm(diffs, 2, 2);
|
||||
dirs = diffs ./ d;
|
||||
% 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)
|
||||
|
||||
% 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');
|
||||
% compute tilt angle
|
||||
tiltAngle = (180 - atan2d(x, targetPos(:, 3) - agentPos(3))); % degrees
|
||||
|
||||
% Membership functions
|
||||
mu_d = obj.distanceMembership(d);
|
||||
mu_t = obj.tiltMembership(angularOffset);
|
||||
mu_t = obj.tiltMembership(tiltAngle);
|
||||
|
||||
value = mu_d .* mu_t; % assume pan membership is always 1
|
||||
end
|
||||
@@ -6,20 +6,14 @@ 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, 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
|
||||
[obj] = initialize(obj, alphaDist, betaDist, alphaTilt, betaTilt);
|
||||
[value] = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos);
|
||||
[f] = plotParameters(obj);
|
||||
end
|
||||
methods (Access = private)
|
||||
x = distanceMembership(obj, d); % used in computing distance factor of sensor performance
|
||||
x = tiltMembership(obj, t); % used in computing tilt factor of sensor performance
|
||||
x = distanceMembership(obj, d);
|
||||
x = tiltMembership(obj, t);
|
||||
end
|
||||
end
|
||||
Submodule
+1
Submodule aerpaw/aerpawlib added at 705fc699ef
@@ -164,7 +164,7 @@ class UAVRunner(BasicRunner):
|
||||
|
||||
# Retry connection up to 10 times (~30 seconds total)
|
||||
reader, writer = None, None
|
||||
for attempt in range(100):
|
||||
for attempt in range(10):
|
||||
try:
|
||||
reader, writer = await asyncio.wait_for(
|
||||
asyncio.open_connection(self.server_ip, self.server_port),
|
||||
|
||||
@@ -12,8 +12,8 @@ tdm:
|
||||
|
||||
# ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
|
||||
origin:
|
||||
lat: 35.72595214250436
|
||||
lon: -78.69917609299937
|
||||
lat: 35.72550610629396
|
||||
lon: -78.70019657805574
|
||||
alt: 0.0 # Alt=0 means ENU z directly becomes target altitude above home
|
||||
# Environment-specific settings
|
||||
environments:
|
||||
@@ -28,11 +28,11 @@ environments:
|
||||
port: 5000
|
||||
|
||||
testbed:
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
|
||||
mavlink:
|
||||
ip: "192.168.32.26"
|
||||
port: 14550
|
||||
# Controller runs on host machine (192.168.X.1, generally)
|
||||
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
|
||||
controller:
|
||||
ip: "192.168.112.1"
|
||||
ip: "192.168.122.1"
|
||||
port: 5000
|
||||
|
||||
@@ -12,8 +12,8 @@ tdm:
|
||||
|
||||
# ENU coordinate system origin (AERPAW Lake Wheeler Road Field)
|
||||
origin:
|
||||
lat: 35.72595214250436
|
||||
lon: -78.69917609299937
|
||||
lat: 35.72550610629396
|
||||
lon: -78.70019657805574
|
||||
alt: 0.0 # Alt=0 means ENU z directly becomes target altitude above home
|
||||
# Environment-specific settings
|
||||
environments:
|
||||
@@ -28,11 +28,11 @@ environments:
|
||||
port: 5000
|
||||
|
||||
testbed:
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects to us (UDP)
|
||||
# AERPAW testbed: E-VM listens, MAVLink Filter connects TO us (UDP)
|
||||
mavlink:
|
||||
ip: "192.168.32.26"
|
||||
port: 14550
|
||||
# Controller runs on host machine (192.168.X.1, generally)
|
||||
# Controller runs on host machine (192.168.122.1 from E-VM perspective)
|
||||
controller:
|
||||
ip: "192.168.112.1"
|
||||
ip: "192.168.122.1"
|
||||
port: 5000
|
||||
@@ -1,2 +1,2 @@
|
||||
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
|
||||
1, 100, 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
|
||||
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax
|
||||
5, 120, 30.0, 0.1, 1.0, 2.0, 100, 3, "3.0, 3.0", "30.0, 30.0", "80.0, 80.0", "0.25, 0.25", "5.0, 5.0", "0.1, 0.1", "0.0, 0.0, 0.0", "50.0, 50.0, 80.0", "35.0, 35.0", "10, 5, 5, 10", 0.15, "5.0, 10.0, 45.0, 15.0, 10.0, 35.0", 1, "2.0, 15.0, 0.0", "25.0, 25.0, 50.0"
|
||||
|
@@ -1,2 +0,0 @@
|
||||
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, 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
|
||||
|
@@ -1,2 +0,0 @@
|
||||
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
|
||||
|
@@ -1,2 +0,0 @@
|
||||
timestep, maxIter, minAlt, discretizationStep, protectedRange, initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange, alphaDist, betaDist, alphaTilt, betaTilt, domainMin, domainMax, objectivePos, objectiveVar, sensorPerformanceMinimum, initialPositions, numObstacles, obstacleMin, obstacleMax, useDoubleIntegrator, dampingCoeff, useFixedTopology
|
||||
1, 100, 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
|
||||
|
@@ -1,2 +0,0 @@
|
||||
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, "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
|
||||
|
+120
-214
@@ -133,46 +133,6 @@
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="27" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="28" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="29" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="30" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="31" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="32" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
<Size type="coderapp.internal.codertype.Dimension"/>
|
||||
</Types>
|
||||
<Types id="33" type="coderapp.internal.codertype.PrimitiveType">
|
||||
<ClassName>int32</ClassName>
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+4
-49
@@ -7,8 +7,7 @@ coder.extrinsic('disp', 'readScenarioCsv');
|
||||
|
||||
% Maximum clients supported (one initial position per UAV)
|
||||
MAX_CLIENTS = 4;
|
||||
% Two waypoints per UAV: altitude-staggered transit + final position
|
||||
MAX_TARGETS = MAX_CLIENTS * 2;
|
||||
MAX_TARGETS = MAX_CLIENTS;
|
||||
|
||||
% Allocate targets array (MAX_TARGETS x 3)
|
||||
targets = zeros(MAX_TARGETS, 3);
|
||||
@@ -34,31 +33,8 @@ 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
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TRANSIT_ALT_STEP = 25; % vertical separation per UAV (m); must exceed 2*collisionRadius
|
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if ~coder.target('MATLAB')
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for ii = double(totalLoaded):-1:1
|
||||
transitRow = (ii - 1) * 2 + 1;
|
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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];
|
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end
|
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numWaypoints = int32(2);
|
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end
|
||||
|
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% Load guidance scenario from CSV (parameters for guidance_step)
|
||||
NUM_SCENARIO_PARAMS = 55;
|
||||
NUM_SCENARIO_PARAMS = 45;
|
||||
MAX_OBSTACLES_CTRL = int32(8);
|
||||
scenarioParams = zeros(1, NUM_SCENARIO_PARAMS);
|
||||
obstacleMin = zeros(MAX_OBSTACLES_CTRL, 3);
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@@ -102,7 +78,7 @@ for w = 1:numWaypoints
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target = targets(targetIdx, :);
|
||||
|
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if coder.target('MATLAB')
|
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disp(['Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
|
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disp([datestr(now, 'HH:MM:SS'), ' Sending TARGET to client ', num2str(i), ' (waypoint ', num2str(w), '): ', ...
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num2str(target(1)), ',', num2str(target(2)), ',', num2str(target(3))]);
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else
|
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coder.ceval('sendTarget', int32(i), coder.ref(target));
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@@ -149,10 +125,6 @@ guidance_step(positions(1:numClients, :), true, ...
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% Main guidance loop (event-triggered)
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for step = 1:MAX_GUIDANCE_STEPS
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if ~coder.target('MATLAB')
|
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coder.ceval('setGuidanceStep', int32(step), int32(MAX_GUIDANCE_STEPS));
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end
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|
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% Run one guidance step: feed current GPS positions in, get targets out
|
||||
nextPositions = guidance_step(positions(1:numClients, :), false, ...
|
||||
scenarioParams, obstacleMin, obstacleMax, numObstacles);
|
||||
@@ -163,7 +135,7 @@ for step = 1:MAX_GUIDANCE_STEPS
|
||||
if ~coder.target('MATLAB')
|
||||
coder.ceval('sendTarget', int32(i), coder.ref(target));
|
||||
else
|
||||
disp(['[step ', num2str(step), '] target UAV ', num2str(i), ': ', num2str(target)]);
|
||||
disp([datestr(now, 'HH:MM:SS'), ' [guidance] target UAV ', num2str(i), ': ', num2str(target)]);
|
||||
end
|
||||
end
|
||||
|
||||
@@ -192,26 +164,9 @@ 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')
|
||||
|
||||
+14
-29
@@ -29,9 +29,6 @@ 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
|
||||
@@ -94,34 +91,26 @@ if isInit
|
||||
BETA_TILT_VEC = scenarioParams(29:32);
|
||||
DOMAIN_MIN = scenarioParams(33:35);
|
||||
DOMAIN_MAX = scenarioParams(36:38);
|
||||
NUM_OBJ_COMPONENTS = int32(scenarioParams(39));
|
||||
OBJECTIVE_POS_FLAT = scenarioParams(40:43); % [x1,y1,x2,y2]; zero-padded if N=1
|
||||
OBJECTIVE_VAR_FLAT = scenarioParams(44:51); % [v11,v12,v21,v22 per component]
|
||||
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(52);
|
||||
USE_DOUBLE_INTEGRATOR = logical(scenarioParams(53));
|
||||
DAMPING_COEFF = scenarioParams(54);
|
||||
USE_FIXED_TOPOLOGY = logical(scenarioParams(55));
|
||||
OBJECTIVE_GROUND_POS = scenarioParams(39:40);
|
||||
OBJECTIVE_VAR = reshape(scenarioParams(41:44), 2, 2);
|
||||
SENSOR_PERFORMANCE_MINIMUM = scenarioParams(45);
|
||||
|
||||
% --- Build domain geometry ---
|
||||
dom = rectangularPrism;
|
||||
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
|
||||
|
||||
% --- Build sensing objective: sum of N bivariate Gaussians (codegen-compatible) ---
|
||||
% --- Build sensing objective (inline Gaussian; codegen-compatible) ---
|
||||
dom.objective = sensingObjective;
|
||||
xGrid = unique([DOMAIN_MIN(1):DISCRETIZATION_STEP:DOMAIN_MAX(1), DOMAIN_MAX(1)]);
|
||||
yGrid = unique([DOMAIN_MIN(2):DISCRETIZATION_STEP:DOMAIN_MAX(2), DOMAIN_MAX(2)]);
|
||||
[gridX, gridY] = meshgrid(xGrid, yGrid);
|
||||
objValues = zeros(size(gridX));
|
||||
for kk = 1:NUM_OBJ_COMPONENTS
|
||||
pos_k = OBJECTIVE_POS_FLAT((kk-1)*2+1 : (kk-1)*2+2);
|
||||
var_k = reshape(OBJECTIVE_VAR_FLAT((kk-1)*4+1 : (kk-1)*4+4), 2, 2);
|
||||
dx = gridX - pos_k(1);
|
||||
dy = gridY - pos_k(2);
|
||||
ov_a = var_k(1,1); ov_b = var_k(1,2);
|
||||
ov_c = var_k(2,1); ov_d = var_k(2,2);
|
||||
ov_det = ov_a * ov_d - ov_b * ov_c;
|
||||
objValues = objValues + exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
|
||||
end
|
||||
dx = gridX - OBJECTIVE_GROUND_POS(1);
|
||||
dy = gridY - OBJECTIVE_GROUND_POS(2);
|
||||
% Bivariate Gaussian using objectiveVar covariance matrix (avoids inv())
|
||||
ov_a = OBJECTIVE_VAR(1,1); ov_b = OBJECTIVE_VAR(1,2);
|
||||
ov_c = OBJECTIVE_VAR(2,1); ov_d = OBJECTIVE_VAR(2,2);
|
||||
ov_det = ov_a * ov_d - ov_b * ov_c;
|
||||
objValues = exp((-0.5 / ov_det) .* (ov_d .* dx.*dx - (ov_b + ov_c) .* dx.*dy + ov_a .* dy.*dy));
|
||||
dom.objective = dom.objective.initializeWithValues(objValues, dom, ...
|
||||
DISCRETIZATION_STEP, PROTECTED_RANGE, SENSOR_PERFORMANCE_MINIMUM);
|
||||
|
||||
@@ -157,8 +146,7 @@ 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, ...
|
||||
USE_DOUBLE_INTEGRATOR, DAMPING_COEFF, USE_FIXED_TOPOLOGY);
|
||||
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
|
||||
end
|
||||
|
||||
% On the init call return current positions unchanged
|
||||
@@ -188,9 +176,7 @@ else
|
||||
sim.timestepIndex = sim.timestepIndex + 1;
|
||||
|
||||
% 3. Update communications topology (Lesser Neighbour Assignment)
|
||||
if ~sim.useFixedTopology
|
||||
sim = sim.lesserNeighbor();
|
||||
end
|
||||
sim = sim.lesserNeighbor();
|
||||
|
||||
% 4. Compute Voronoi partitioning
|
||||
sim.partitioning = sim.agents{1}.partition(sim.agents, sim.domain.objective);
|
||||
@@ -198,8 +184,7 @@ 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.useDoubleIntegrator, sim.dampingCoeff, sim.timestep, sim.optimizeSensorPointing);
|
||||
sim.timestepIndex, ii, sim.agents);
|
||||
end
|
||||
|
||||
% 6. Apply CBF safety filter (collision / comms / domain constraints via QP)
|
||||
|
||||
+31
-120
@@ -16,44 +16,6 @@
|
||||
|
||||
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() {}
|
||||
@@ -222,13 +184,9 @@ static int readScenarioDataRow(const char* filename, char* line, int lineSize) {
|
||||
// 28-31: betaTilt[1:4]
|
||||
// 32-34: domainMin (east, north, up)
|
||||
// 35-37: domainMax (east, north, up)
|
||||
// 38 : numObjectiveComponents (1 or 2; inferred from objectivePos field length)
|
||||
// 39-42: objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
|
||||
// 43-50: objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
|
||||
// 51 : sensorPerformanceMinimum (CSV column 18)
|
||||
// 52 : useDoubleIntegrator (CSV column 23)
|
||||
// 53 : dampingCoeff (CSV column 24)
|
||||
// 54 : useFixedTopology (CSV column 25)
|
||||
// 38-39: objectivePos (east, north)
|
||||
// 40-43: objectiveVar (2x2 col-major: v11, v12, v21, v22)
|
||||
// 44 : sensorPerformanceMinimum
|
||||
// Returns 1 on success, 0 on failure.
|
||||
int loadScenario(const char* filename, double* params) {
|
||||
char line[4096];
|
||||
@@ -240,8 +198,8 @@ int loadScenario(const char* filename, double* params) {
|
||||
|
||||
char* fields[32];
|
||||
int nf = splitCSVRow(copy, fields, 32);
|
||||
if (nf < 26) {
|
||||
fprintf(stderr, "loadScenario: expected >=26 columns, got %d\n", nf);
|
||||
if (nf < 19) {
|
||||
fprintf(stderr, "loadScenario: expected >=19 columns, got %d\n", nf);
|
||||
return 0;
|
||||
}
|
||||
|
||||
@@ -306,78 +264,34 @@ int loadScenario(const char* filename, double* params) {
|
||||
}
|
||||
}
|
||||
|
||||
// objectivePos: column 16 — 2 values per component (up to 2 components).
|
||||
// Infer numObjectiveComponents from the number of values parsed.
|
||||
// objectivePos: column 16
|
||||
{
|
||||
char tmp[256]; strncpy(tmp, fields[16], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
char* t = trimField(tmp);
|
||||
double posVals[4] = {0, 0, 0, 0};
|
||||
int posCount = 0;
|
||||
char* tok = strtok(t, ",");
|
||||
while (tok && posCount < 4) {
|
||||
posVals[posCount++] = atof(tok);
|
||||
tok = strtok(nullptr, ",");
|
||||
}
|
||||
// Check for a 5th token — would mean > 2 components
|
||||
if (tok) {
|
||||
fprintf(stderr, "loadScenario: at most 2 objective Gaussian components supported (objectivePos has >4 values)\n");
|
||||
if (sscanf(t, "%lf , %lf", ¶ms[38], ¶ms[39]) != 2) {
|
||||
fprintf(stderr, "loadScenario: failed to parse objectivePos: %s\n", t);
|
||||
return 0;
|
||||
}
|
||||
if (posCount == 0 || posCount % 2 != 0) {
|
||||
fprintf(stderr, "loadScenario: objectivePos must have 2 or 4 values, got %d\n", posCount);
|
||||
return 0;
|
||||
}
|
||||
int nObj = posCount / 2;
|
||||
params[38] = (double)nObj;
|
||||
for (int k = 0; k < 4; k++) params[39 + k] = posVals[k]; // zero-padded for nObj=1
|
||||
}
|
||||
|
||||
// objectiveVar: column 17 — 4 values per component (v11,v12,v21,v22).
|
||||
// objectiveVar: column 17, format "v11, v12, v21, v22"
|
||||
{
|
||||
char tmp[512]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
char tmp[256]; strncpy(tmp, fields[17], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
char* t = trimField(tmp);
|
||||
int nObj = (int)params[38];
|
||||
double varVals[8] = {0, 0, 0, 0, 0, 0, 0, 0};
|
||||
int varCount = 0;
|
||||
char* tok = strtok(t, ",");
|
||||
while (tok && varCount < 8) {
|
||||
varVals[varCount++] = atof(tok);
|
||||
tok = strtok(nullptr, ",");
|
||||
}
|
||||
if (varCount != nObj * 4) {
|
||||
fprintf(stderr, "loadScenario: objectiveVar has %d values but expected %d (4 per component)\n",
|
||||
varCount, nObj * 4);
|
||||
if (sscanf(t, "%lf , %lf , %lf , %lf", ¶ms[40], ¶ms[41], ¶ms[42], ¶ms[43]) != 4) {
|
||||
fprintf(stderr, "loadScenario: failed to parse objectiveVar: %s\n", t);
|
||||
return 0;
|
||||
}
|
||||
for (int k = 0; k < 8; k++) params[43 + k] = varVals[k]; // zero-padded for nObj=1
|
||||
}
|
||||
|
||||
// sensorPerformanceMinimum: column 18
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[18], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[51] = atof(trimField(tmp));
|
||||
params[44] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// useDoubleIntegrator: column 23
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[23], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[52] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// dampingCoeff: column 24
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[24], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[53] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
// useFixedTopology: column 25
|
||||
{
|
||||
char tmp[64]; strncpy(tmp, fields[25], sizeof(tmp) - 1); tmp[sizeof(tmp)-1] = '\0';
|
||||
params[54] = atof(trimField(tmp));
|
||||
}
|
||||
|
||||
printf("Loaded scenario: domain [%g,%g,%g] to [%g,%g,%g], %d objective component(s)\n",
|
||||
params[32], params[33], params[34], params[35], params[36], params[37], (int)params[38]);
|
||||
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;
|
||||
}
|
||||
|
||||
@@ -516,22 +430,18 @@ static const char* messageTypeName(uint8_t msgType) {
|
||||
}
|
||||
}
|
||||
|
||||
// Send a single-byte message type to a client (no logging)
|
||||
static int sendMessageTypeRaw(int clientId, int msgType) {
|
||||
// Send a single-byte message type to a client
|
||||
int sendMessageType(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;
|
||||
}
|
||||
|
||||
// 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";
|
||||
std::cout << "Sent " << messageTypeName(msg) << " to client " << clientId << "\n";
|
||||
return 1;
|
||||
}
|
||||
|
||||
@@ -550,7 +460,13 @@ int sendTarget(int clientId, const double* coords) {
|
||||
return 0;
|
||||
}
|
||||
|
||||
std::cout << logPrefix() << "Sent TARGET to client " << clientId << ": "
|
||||
// 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 << ": "
|
||||
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
|
||||
return 1;
|
||||
}
|
||||
@@ -598,36 +514,31 @@ 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++) {
|
||||
sendMessageTypeRaw(i, 6); // GUIDANCE_TOGGLE = 6
|
||||
sendMessageType(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 (!sendMessageTypeRaw(i, 7)) return 0; // REQUEST_POSITION = 7
|
||||
if (!sendMessageType(i, 7)) return 0; // REQUEST_POSITION = 7
|
||||
}
|
||||
std::cout << logPrefix() << "Sent REQUEST_POSITION to clients\n";
|
||||
return 1;
|
||||
}
|
||||
|
||||
@@ -662,7 +573,7 @@ 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 << logPrefix() << "Position from client " << (i + 1) << ": "
|
||||
std::cout << "Position from client " << (i + 1) << ": "
|
||||
<< coords[0] << "," << coords[1] << "," << coords[2] << "\n";
|
||||
}
|
||||
return 1;
|
||||
|
||||
@@ -27,14 +27,10 @@ int loadTargets(const char* filename, double* targets, int maxClients);
|
||||
// 28-31 betaTilt[1:4]
|
||||
// 32-34 domainMin
|
||||
// 35-37 domainMax
|
||||
// 38 numObjectiveComponents (1 or 2; inferred from objectivePos field length)
|
||||
// 39-42 objectivePos flat [x1,y1,x2,y2] (4 slots; zero-padded if N=1)
|
||||
// 43-50 objectiveVar flat [v11,v12,v21,v22 per component] (8 slots; zero-padded if N=1)
|
||||
// 51 sensorPerformanceMinimum
|
||||
// 52 useDoubleIntegrator (0=single-integrator, 1=double-integrator)
|
||||
// 53 dampingCoeff
|
||||
// 54 useFixedTopology (0=dynamic lesser-neighbor, 1=fixed)
|
||||
#define NUM_SCENARIO_PARAMS 55
|
||||
// 38-39 objectivePos
|
||||
// 40-43 objectiveVar (2x2 col-major)
|
||||
// 44 sensorPerformanceMinimum
|
||||
#define NUM_SCENARIO_PARAMS 45
|
||||
#define MAX_CLIENTS_PER_PARAM 4
|
||||
// Maximum number of obstacles (upper bound for pre-allocated arrays).
|
||||
#define MAX_OBSTACLES 8
|
||||
@@ -63,7 +59,6 @@ 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
|
||||
|
||||
@@ -1,17 +1,12 @@
|
||||
#include <iostream>
|
||||
#include "controller.h"
|
||||
#include "controller.h"
|
||||
#include "controller_impl.h" // TCP implementation header
|
||||
|
||||
int main() {
|
||||
// Derive numClients from initialPositions in scenario.csv
|
||||
double targets[MAX_CLIENTS_PER_PARAM * 3];
|
||||
int numClients = loadInitialPositions("config/scenario.csv",
|
||||
targets, MAX_CLIENTS_PER_PARAM);
|
||||
if (numClients < 1) {
|
||||
std::cerr << "Failed to parse numClients from scenario.csv\n";
|
||||
return 1;
|
||||
}
|
||||
std::cout << "Parsed " << numClients << " UAV(s) from scenario.csv\n";
|
||||
// Number of clients to handle
|
||||
int numClients = 2; // for now
|
||||
|
||||
std::cout << "Initializing TCP server...\n";
|
||||
|
||||
// Call MATLAB-generated server function
|
||||
controller(numClients);
|
||||
|
||||
@@ -267,10 +267,6 @@ class CSwSNRRX(gr.top_block):
|
||||
'/root/Quality', num_uavs, slot_duration, guard_interval)
|
||||
self.blocks_file_sink_0 = TdmTaggedFileSink(
|
||||
'/root/Power', num_uavs, slot_duration, guard_interval)
|
||||
self.blocks_file_sink_noisefloor = TdmTaggedFileSink(
|
||||
'/root/NoiseFloor', num_uavs, slot_duration, guard_interval)
|
||||
self._freqoffset_file = open('/root/FreqOffset', 'w')
|
||||
self._freqoffset_file.write('tx_uav_id,value\n')
|
||||
self.blocks_divide_xx_0 = blocks.divide_ff(1)
|
||||
self.blocks_complex_to_real_0_0 = blocks.complex_to_real(1)
|
||||
self.blocks_complex_to_real_0 = blocks.complex_to_real(1)
|
||||
@@ -314,7 +310,6 @@ class CSwSNRRX(gr.top_block):
|
||||
self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_add_const_vxx_0, 0))
|
||||
self.connect((self.blocks_nlog10_ff_0_0, 0), (self.blocks_sub_xx_0, 0))
|
||||
self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_sub_xx_0, 1))
|
||||
self.connect((self.blocks_nlog10_ff_0_0_0, 0), (self.blocks_file_sink_noisefloor, 0))
|
||||
self.connect((self.blocks_stream_to_vector_0_0, 0), (self.epy_block_0, 0))
|
||||
self.connect((self.blocks_sub_xx_0, 0), (self.blocks_file_sink_0_0_0, 0))
|
||||
self.connect((self.blocks_vector_to_stream_0_0, 0), (self.blocks_keep_m_in_n_0, 0))
|
||||
@@ -326,26 +321,6 @@ class CSwSNRRX(gr.top_block):
|
||||
self.connect((self.freq_xlating_fft_filter_ccc_0_0, 0), (self.blocks_stream_to_vector_0_0, 0))
|
||||
self.connect((self.uhd_usrp_source_0, 0), (self.blocks_multiply_xx_0, 0))
|
||||
|
||||
##################################################
|
||||
# Frequency offset polling thread
|
||||
##################################################
|
||||
def _freq_offset_probe():
|
||||
frame_dur = slot_duration * num_uavs
|
||||
while True:
|
||||
val = self.digital_fll_band_edge_cc_0_0.get_frequency()
|
||||
freq_hz = val * samp_rate / (2 * math.pi)
|
||||
now = time.time()
|
||||
slot_time = now % frame_dur
|
||||
current_slot = int(slot_time / slot_duration)
|
||||
time_into_slot = slot_time - current_slot * slot_duration
|
||||
tx_id = -1 if time_into_slot < guard_interval else current_slot
|
||||
self._freqoffset_file.write(f'{tx_id},{freq_hz}\n')
|
||||
self._freqoffset_file.flush()
|
||||
time.sleep(0.01)
|
||||
_freq_offset_thread = threading.Thread(target=_freq_offset_probe)
|
||||
_freq_offset_thread.daemon = True
|
||||
_freq_offset_thread.start()
|
||||
|
||||
|
||||
def get_args(self):
|
||||
return self.args
|
||||
|
||||
@@ -20,4 +20,4 @@ else
|
||||
fi
|
||||
|
||||
cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
|
||||
python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
|
||||
python3 CSwSNRRX.py --freq $RX_FREQ --gainrx $GAIN_RX --noise 0 --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS
|
||||
@@ -20,4 +20,4 @@ else
|
||||
fi
|
||||
|
||||
cd $PROFILE_DIR"/SDR_control/Channel_Sounderv3"
|
||||
python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS "$@"
|
||||
python3 CSwSNRTX.py --freq $TX_FREQ --gaintx $GAIN_TX --args $ARGS --offset $OFFSET --samp-rate $SAMP_RATE --sps $SPS
|
||||
@@ -1,16 +1,7 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Drop in replacements for channel sounder scripts
|
||||
cp startchannelsounderRXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
|
||||
cp startchannelsounderTXGRC.sh /root/Profiles/ProfileScripts/Radio/Helpers/.
|
||||
|
||||
cp CSwSNRRX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
|
||||
cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
|
||||
|
||||
# Replace start scripts
|
||||
cp ../scripts/startexperiment.sh /root/.
|
||||
cp ../scripts/startRadio.sh /root/Profiles/ProfileScripts/Radio/.
|
||||
cp ../scripts/startVehicle.sh /root/Profiles/ProfileScripts/Vehicle/.
|
||||
|
||||
echo "REMEMBER! Manually edit startexperiment.sh to point to the correct client.yaml"
|
||||
echo "REMEMBER! Manually copy startexperiment_controller.sh to startexperiment.sh on the fixed node"
|
||||
echo "REMEMBER! Manually copy startVehicle_controller.sh to ~/Profiles/ProfileScripts/Vehicle/startVehicle.sh on the fixed node"
|
||||
cp CSwSNRTX.py /root/Profiles/SDR_control/Channel_Sounderv3/.
|
||||
@@ -1,28 +0,0 @@
|
||||
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
|
||||
@@ -1,8 +1,7 @@
|
||||
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
|
||||
function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel)
|
||||
arguments (Input)
|
||||
logDirs (1, 1) string;
|
||||
seaToGroundLevel (1, 1) double = 110; % measured approximately from USGS national map viewer for the AERPAW test field
|
||||
plotWholeFlight (1, 1) logical = false;
|
||||
end
|
||||
arguments (Output)
|
||||
f (1, 1) matlab.ui.Figure;
|
||||
@@ -29,7 +28,6 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
|
||||
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)
|
||||
@@ -50,10 +48,8 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
|
||||
stopIdx = find(verticalSpeed <= prctile(verticalSpeed, pctThreshold), 1, "last");
|
||||
|
||||
% % Plot whole flight, including setup/cleanup
|
||||
if plotWholeFlight
|
||||
startIdx = 1;
|
||||
stopIdx = length(verticalSpeed);
|
||||
end
|
||||
% startIdx = 1;
|
||||
% stopIdx = length(verticalSpeed);
|
||||
|
||||
% Convert LLA trajectory data to ENU for external analysis
|
||||
% NaN out entries outside the algorithm flight range so they don't plot
|
||||
@@ -61,27 +57,6 @@ function [f, G] = plotGpsLogs(logDirs, seaToGroundLevel, plotWholeFlight)
|
||||
enu(startIdx:stopIdx, :) = lla2enu([G{ii}.Latitude(startIdx:stopIdx), G{ii}.Longitude(startIdx:stopIdx), G{ii}.Altitude(startIdx:stopIdx)], lla0, "flat");
|
||||
enu = array2table(enu, 'VariableNames', ["East", "North", "Up"]);
|
||||
G{ii} = [G{ii}, enu];
|
||||
|
||||
% 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);
|
||||
|
||||
+10
-194
@@ -1,12 +1,9 @@
|
||||
function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
|
||||
function [f, R] = plotRadioLogs(resultsPath)
|
||||
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
|
||||
|
||||
@@ -27,60 +24,18 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
|
||||
R{ii}(bad, :) = [];
|
||||
end
|
||||
|
||||
% Compute path loss from Power (post-processing)
|
||||
% Power = 20*log10(peak_mag) - rxGain; path loss = txGain - rxGain - Power
|
||||
txGain_dB = 76; % from startchannelsounderTXGRC.sh GAIN_TX
|
||||
rxGain_dB = 30; % from startchannelsounderRXGRC.sh GAIN_RX
|
||||
for ii = 1:numel(R)
|
||||
R{ii}.PathLoss = txGain_dB - rxGain_dB - R{ii}.Power;
|
||||
R{ii}.FreqOffset = R{ii}.FreqOffset / 1e6; % Hz to MHz
|
||||
end
|
||||
|
||||
% Build legend labels and color map for up to 4 UAVs
|
||||
nUAV = numel(R);
|
||||
colors = lines(nUAV * nUAV);
|
||||
styles = ["-o", "-s", "-^", "-d", "-v", "-p", "-h", "-<", "->", "-+", "-x", "-*"];
|
||||
|
||||
metricNames = ["SNR", "Power", "Quality", "PathLoss", "NoiseFloor", "FreqOffset"];
|
||||
yLabels = ["SNR (dB)", "Power (dB)", "Quality", "Path Loss (dB)", "Noise Floor (dB)", "Freq Offset (MHz)"];
|
||||
nMetrics = numel(metricNames);
|
||||
metricNames = ["SNR", "Power", "Quality"];
|
||||
yLabels = ["SNR (dB)", "Power (dB)", "Quality"];
|
||||
|
||||
% --- Time-based figure ---
|
||||
f = figure;
|
||||
tl = tiledlayout(nMetrics + 1, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||
tl = tiledlayout(3, 1, 'TileSpacing', 'compact', 'Padding', 'compact');
|
||||
|
||||
% 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
|
||||
for mi = 1:numel(metricNames)
|
||||
ax = nexttile(tl);
|
||||
hold(ax, 'on');
|
||||
grid(ax, 'on');
|
||||
@@ -93,32 +48,23 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
|
||||
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);
|
||||
|
||||
if isempty(rows)
|
||||
% Skip if all NaN for this metric
|
||||
if all(isnan(vals))
|
||||
continue;
|
||||
end
|
||||
|
||||
si = mod(ci - 1, numel(styles)) + 1;
|
||||
plot(ax, rows.Timestamp, vals, styles(si), ...
|
||||
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 0.5);
|
||||
'Color', colors(ci, :), 'MarkerSize', 3, 'LineWidth', 1);
|
||||
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 == nMetrics
|
||||
if mi == numel(metricNames)
|
||||
xlabel(ax, 'Time');
|
||||
end
|
||||
legend(ax, legendEntries, 'Location', 'best');
|
||||
@@ -126,134 +72,4 @@ function [f, fDist, R] = plotRadioLogs(resultsPath, G, tLim)
|
||||
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
|
||||
end
|
||||
@@ -1,32 +0,0 @@
|
||||
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
|
||||
@@ -2,20 +2,21 @@ function R = readRadioLogs(logPath)
|
||||
arguments (Input)
|
||||
logPath (1, 1) string {isfolder(logPath)};
|
||||
end
|
||||
|
||||
arguments (Output)
|
||||
R (:, 8) table;
|
||||
R (:, 6) table;
|
||||
end
|
||||
|
||||
% Extract receiving UAV ID from directory name (e.g. "uav0_..." → 0)
|
||||
[~, dirName] = fileparts(logPath);
|
||||
rxID = int32(sscanf(dirName, 'uav%d'));
|
||||
|
||||
metrics = ["quality", "snr", "power", "noisefloor", "freqoffset"];
|
||||
metrics = ["quality", "snr", "power"];
|
||||
logs = dir(logPath);
|
||||
logs = logs(endsWith({logs(:).name}, metrics + "_log.txt"));
|
||||
|
||||
R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), zeros(0,1), ...
|
||||
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
|
||||
R = table(datetime.empty(0,1), zeros(0,1,'int32'), zeros(0,1,'int32'), zeros(0,1), zeros(0,1), zeros(0,1), ...
|
||||
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
|
||||
|
||||
for ii = 1:numel(logs)
|
||||
filepath = fullfile(logs(ii).folder, logs(ii).name);
|
||||
@@ -30,39 +31,25 @@ function R = readRadioLogs(logPath)
|
||||
end
|
||||
|
||||
fid = fopen(filepath, 'r');
|
||||
% Skip header lines: some files have 2 tail-error lines + 1 column
|
||||
% header ("tx_uav_id,value"), others start with data immediately.
|
||||
% Read until a line that looks like a data record, then rewind to it.
|
||||
dataPattern = '^\[\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}\.\d+\] [-\d]';
|
||||
linePos = ftell(fid);
|
||||
while true
|
||||
line = fgetl(fid);
|
||||
if ~ischar(line)
|
||||
break; % EOF
|
||||
end
|
||||
if ~isempty(regexp(line, dataPattern, 'once'))
|
||||
fseek(fid, linePos, 'bof'); % rewind to start of this line
|
||||
break;
|
||||
end
|
||||
linePos = ftell(fid);
|
||||
% Skip 3 lines: 2 junk (tail errors) + 1 header (tx_uav_id,value)
|
||||
for k = 1:3
|
||||
fgetl(fid);
|
||||
end
|
||||
data = textscan(fid, '[%26c] %d,%f');
|
||||
fclose(fid);
|
||||
|
||||
ts = datetime(cellstr(data{1}), 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
|
||||
ts = datetime(data{1}, 'InputFormat', 'yyyy-MM-dd HH:mm:ss.SSSSSS');
|
||||
txId = int32(data{2});
|
||||
val = data{3};
|
||||
|
||||
n = numel(ts);
|
||||
t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), NaN(n,1), ...
|
||||
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality", "NoiseFloor", "FreqOffset"]);
|
||||
t = table(ts, txId, repmat(rxID, n, 1), NaN(n,1), NaN(n,1), NaN(n,1), ...
|
||||
'VariableNames', ["Timestamp", "TxUAVID", "RxUAVID", "SNR", "Power", "Quality"]);
|
||||
|
||||
switch metric
|
||||
case "snr", t.SNR = val;
|
||||
case "power", t.Power = val;
|
||||
case "quality", t.Quality = val;
|
||||
case "noisefloor", t.NoiseFloor = val;
|
||||
case "freqoffset", t.FreqOffset = val;
|
||||
case "snr", t.SNR = val;
|
||||
case "power", t.Power = val;
|
||||
case "quality", t.Quality = val;
|
||||
end
|
||||
|
||||
R = [R; t]; %#ok<AGROW>
|
||||
@@ -70,40 +57,6 @@ 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, :) = [];
|
||||
|
||||
|
||||
@@ -1,16 +1,12 @@
|
||||
%% 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);
|
||||
resultsPath = fullfile(matlab.project.rootProject().RootFolder, "sandbox", "t1"); % Define path to results copied from AERPAW platform
|
||||
|
||||
% Plot GPS logged data and scenario information (domain, objective, obstacles)
|
||||
seaToGroundLevel = 110; % measured approximately from USGS national map viewer
|
||||
plotWholeFlight = true; % do not attempt to automatically trim initial and final positioning and landing from flight plot (buggy)
|
||||
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel, true);
|
||||
[fGlobe, G] = plotGpsLogs(resultsPath, seaToGroundLevel);
|
||||
|
||||
% Plot radio statistics (time-based and distance-based)
|
||||
[fRadio, fRadioDist, R] = plotRadioLogs(resultsPath, G, controller.timestamp([1, end]));
|
||||
% Plot radio statistics
|
||||
[fRadio, R] = plotRadioLogs(resultsPath);
|
||||
|
||||
%% Run simulation
|
||||
% Run miSim using same AERPAW scenario definition CSV
|
||||
@@ -25,7 +21,7 @@ makeVideo = true;
|
||||
% Define scenario according to CSV specification
|
||||
domain = rectangularPrism;
|
||||
domain = domain.initialize([params.domainMin; params.domainMax], REGION_TYPE.DOMAIN, "Domain");
|
||||
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [1, 2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
|
||||
domain.objective = domain.objective.initialize(objectiveFunctionWrapper(params.objectivePos, reshape(params.objectiveVar, [2 2])), domain, params.discretizationStep, params.protectedRange, params.sensorPerformanceMinimum);
|
||||
|
||||
agents = cell(size(params.initialPositions, 2) / 3, 1);
|
||||
for ii = 1:size(agents, 1)
|
||||
@@ -37,7 +33,7 @@ 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, 5.0, 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, sprintf("Agent %d", ii), plotCommsGeometry);
|
||||
end
|
||||
|
||||
% Create obstacles
|
||||
@@ -64,12 +60,9 @@ 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(inRange), G{ii}.North(inRange), G{ii}.Up(inRange) + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
|
||||
plot3(comparison.Children(1).Children(sim.spatialPlotIndices(jj)), G{ii}.East, G{ii}.North, G{ii}.Up + seaToGroundLevel, 'Color', 'r', 'LineWidth', 1);
|
||||
hold(comparison.Children.Children(sim.spatialPlotIndices(jj)), "off");
|
||||
end
|
||||
end
|
||||
@@ -1,29 +0,0 @@
|
||||
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
|
||||
+3
-3
@@ -32,8 +32,8 @@ else
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# Client config file: 2nd argument > AERPAW_CLIENT_CONFIG env var > default
|
||||
CONFIG_FILE="${2:-${AERPAW_CLIENT_CONFIG:-config/client.yaml}}"
|
||||
# Client config file (optional 2nd argument)
|
||||
CONFIG_FILE="${2:-config/client.yaml}"
|
||||
if [ ! -f "$CONFIG_FILE" ]; then
|
||||
echo "Error: Config file not found: $CONFIG_FILE"
|
||||
exit 1
|
||||
@@ -59,7 +59,7 @@ echo "[run_uav] MAVLink connection: $CONN"
|
||||
|
||||
# Run via aerpawlib
|
||||
echo "[run_uav] Starting UAV runner..."
|
||||
python3 -u -m aerpawlib \
|
||||
python3 -m aerpawlib \
|
||||
--script client.uav_runner \
|
||||
--conn "$CONN" \
|
||||
--vehicle drone
|
||||
@@ -1,100 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
# Derive number of UAVs from scenario.csv
|
||||
NUM_UAVS=$(python3 -c "
|
||||
import csv, os
|
||||
csv_path = '/root/miSim/aerpaw/config/scenario.csv'
|
||||
with open(csv_path, 'r') as f:
|
||||
reader = csv.reader(f, skipinitialspace=True)
|
||||
header = [h.strip() for h in next(reader)]
|
||||
row = next(reader)
|
||||
col = header.index('initialPositions')
|
||||
vals = [v.strip() for v in row[col].strip().split(',') if v.strip()]
|
||||
print(len(vals) // 3)
|
||||
" 2>/dev/null || echo 0)
|
||||
|
||||
cd $PROFILE_DIR"/ProfileScripts/Radio/Helpers"
|
||||
|
||||
if [ "$NUM_UAVS" -eq 2 ]; then
|
||||
# Direct 1-to-1 mode: UAV 0 = TX only, UAV 1 = RX only
|
||||
echo "[Radio] 2-UAV direct mode: UAV_ID=$UAV_ID"
|
||||
|
||||
if [ "$UAV_ID" -eq 0 ]; then
|
||||
# TX only (--num-uavs 1 disables TDM muting)
|
||||
screen -S txGRC -dm \
|
||||
bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh --num-uavs 1 \
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
|
||||
else
|
||||
# RX only (--num-uavs 1 disables TDM tagging)
|
||||
screen -S rxGRC -dm \
|
||||
bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh --num-uavs 1 \
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
|
||||
|
||||
screen -S power -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/Power\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
|
||||
|
||||
screen -S quality -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/Quality\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
|
||||
|
||||
screen -S snr -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/SNR\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
|
||||
|
||||
screen -S noisefloor -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
|
||||
|
||||
screen -S freqoffset -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
|
||||
fi
|
||||
else
|
||||
# 3+ UAVs: full TDM mode — every node runs both TX and RX
|
||||
echo "[Radio] TDM mode: $NUM_UAVS UAVs, UAV_ID=$UAV_ID"
|
||||
|
||||
screen -S rxGRC -dm \
|
||||
bash -c "stdbuf -oL -eL ./startchannelsounderRXGRC.sh \
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsounderrxgrc_log.txt"
|
||||
|
||||
screen -S power -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/Power\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_power_log.txt"
|
||||
|
||||
screen -S quality -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/Quality\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_quality_log.txt"
|
||||
|
||||
screen -S snr -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/SNR\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_snr_log.txt"
|
||||
|
||||
screen -S noisefloor -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/NoiseFloor\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_noisefloor_log.txt"
|
||||
|
||||
screen -S freqoffset -dm \
|
||||
bash -c "stdbuf -oL -eL tail -F /root/FreqOffset\
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_freqoffset_log.txt"
|
||||
|
||||
screen -S txGRC -dm \
|
||||
bash -c "stdbuf -oL -eL ./startchannelsounderTXGRC.sh \
|
||||
2>&1 | ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_radio_channelsoundertxgrc_log.txt"
|
||||
fi
|
||||
|
||||
cd -
|
||||
@@ -1,30 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
### Sample GPS logger portion
|
||||
# use vehicle type generic to skip the arming requirement
|
||||
export VEHICLE_TYPE="${VEHICLE_TYPE:-generic}"
|
||||
|
||||
# GPS Logger sample application (this does not move the vehicle)
|
||||
|
||||
#cd $PROFILE_DIR"/ProfileScripts/Vehicle/Helpers"
|
||||
#
|
||||
#screen -S vehicle -dm \
|
||||
# bash -c "stdbuf -oL -eL ./gpsLoggerHelper.sh \
|
||||
# 2> >(ts $TS_FORMAT >> $RESULTS_DIR/${LOG_PREFIX}_vehicle_log_err.txt) \
|
||||
# | ts $TS_FORMAT \
|
||||
# | tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"
|
||||
#
|
||||
#cd -
|
||||
|
||||
### Actual control portion (custom)
|
||||
export VEHICLE_TYPE="${VEHICLE_TYPE:-drone}" # out of rover, drone, generic
|
||||
|
||||
cd /root/miSim/aerpaw
|
||||
|
||||
# Use screen/ts/tee aerpawism from sample script
|
||||
screen -S vehicle -dm \
|
||||
bash -c "stdbuf -oL -eL ./run_uav.sh testbed \
|
||||
| ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_vehicle_log.txt"
|
||||
|
||||
cd -
|
||||
@@ -1,11 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
cd /root/miSim/aerpaw
|
||||
|
||||
# Compile controller
|
||||
/bin/bash compile.sh
|
||||
|
||||
# Run controller
|
||||
./build/controller_app
|
||||
|
||||
cd -
|
||||
@@ -1,50 +0,0 @@
|
||||
#!/bin/bash
|
||||
/root/stopexperiment.sh
|
||||
|
||||
source /root/.ap-set-experiment-env.sh
|
||||
source /root/.bashrc
|
||||
|
||||
# set path to client config YAML
|
||||
export AERPAW_CLIENT_CONFIG=/root/miSim/aerpaw/config/client1.yaml
|
||||
|
||||
export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
|
||||
export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
|
||||
export PYTHONPATH=/usr/local/lib/python3/dist-packages/
|
||||
export EXP_NUMBER=${EXP_NUMBER:-1}
|
||||
|
||||
if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
|
||||
export VEHICLE_TYPE=drone
|
||||
elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
|
||||
export VEHICLE_TYPE=rover
|
||||
else
|
||||
export VEHICLE_TYPE=none
|
||||
fi
|
||||
|
||||
if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
|
||||
export LAUNCH_MODE=EMULATION
|
||||
elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
|
||||
export LAUNCH_MODE=TESTBED
|
||||
else
|
||||
export LAUNCH_MODE=none
|
||||
fi
|
||||
|
||||
# prepare results directory
|
||||
export UAV_ID=$(python3 -c "import yaml; print(yaml.safe_load(open('$AERPAW_CLIENT_CONFIG'))['uav_id'])")
|
||||
export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
|
||||
export RESULTS_DIR="/root/Results/uav${UAV_ID}_${RESULTS_DIR_TIMESTAMP}"
|
||||
mkdir -p "$RESULTS_DIR"
|
||||
|
||||
export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
|
||||
export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
|
||||
|
||||
export TX_FREQ=3.32e9
|
||||
export RX_FREQ=3.32e9
|
||||
|
||||
export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
|
||||
cd $PROFILE_DIR"/ProfileScripts"
|
||||
|
||||
./Radio/startRadio.sh
|
||||
#./Traffic/startTraffic.sh
|
||||
./Vehicle/startVehicle.sh
|
||||
|
||||
schedule_stop.sh 30
|
||||
@@ -1,47 +0,0 @@
|
||||
#!/bin/bash
|
||||
/root/stopexperiment.sh
|
||||
|
||||
source /root/.ap-set-experiment-env.sh
|
||||
source /root/.bashrc
|
||||
|
||||
export AERPAW_REPO=${AERPAW_REPO:-/root/AERPAW-Dev}
|
||||
export AERPAW_PYTHON=${AERPAW_PYTHON:-python3}
|
||||
export PYTHONPATH=/usr/local/lib/python3/dist-packages/
|
||||
export EXP_NUMBER=${EXP_NUMBER:-1}
|
||||
|
||||
if [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_uav" ]; then
|
||||
export VEHICLE_TYPE=drone
|
||||
elif [ "$AP_EXPENV_THIS_CONTAINER_NODE_VEHICLE" == "vehicle_ugv" ]; then
|
||||
export VEHICLE_TYPE=rover
|
||||
else
|
||||
export VEHICLE_TYPE=none
|
||||
fi
|
||||
|
||||
if [ "$AP_EXPENV_SESSION_ENV" == "Virtual" ]; then
|
||||
export LAUNCH_MODE=EMULATION
|
||||
elif [ "$AP_EXPENV_SESSION_ENV" == "Testbed" ]; then
|
||||
export LAUNCH_MODE=TESTBED
|
||||
else
|
||||
export LAUNCH_MODE=none
|
||||
fi
|
||||
|
||||
# prepare results directory
|
||||
export RESULTS_DIR_TIMESTAMP=$(date +%Y-%m-%d_%H_%M_%S)
|
||||
export RESULTS_DIR="/root/Results/controller_${RESULTS_DIR_TIMESTAMP}"
|
||||
mkdir -p "$RESULTS_DIR"
|
||||
|
||||
export TS_FORMAT="${TS_FORMAT:-'[%Y-%m-%d %H:%M:%.S]'}"
|
||||
export LOG_PREFIX="$(date +%Y-%m-%d_%H_%M_%S)"
|
||||
|
||||
export TX_FREQ=3.32e9
|
||||
export RX_FREQ=3.32e9
|
||||
|
||||
export PROFILE_DIR=$AERPAW_REPO"/AHN/E-VM/Profile_software"
|
||||
cd $PROFILE_DIR"/ProfileScripts"
|
||||
|
||||
screen -S controller -dm \
|
||||
bash -c "stdbuf -oL -eL ./Vehicle/startVehicle.sh \
|
||||
| ts $TS_FORMAT \
|
||||
| tee $RESULTS_DIR/$LOG_PREFIX\_controller_log.txt"
|
||||
|
||||
schedule_stop.sh 30
|
||||
@@ -6,11 +6,9 @@ classdef cone
|
||||
label = "";
|
||||
|
||||
% Spatial
|
||||
center = NaN;
|
||||
radius = NaN;
|
||||
height = NaN;
|
||||
tilt = 0; % degrees, 0=nadir 90=horizon
|
||||
azimuth = 0; % degrees, 0=+Y 90=+X clockwise
|
||||
center = NaN;
|
||||
radius = NaN;
|
||||
height = NaN;
|
||||
|
||||
% Plotting
|
||||
surface;
|
||||
|
||||
@@ -1,23 +1,19 @@
|
||||
function obj = initialize(obj, center, radius, height, tag, label, tilt, azimuth)
|
||||
function obj = initialize(obj, center, radius, height, tag, label)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, "cone")};
|
||||
center (1, 3) double;
|
||||
radius (1, 1) double;
|
||||
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;
|
||||
obj (1, 1) {mustBeA(obj, "cone")};
|
||||
center (1, 3) double;
|
||||
radius (1, 1) double;
|
||||
height (1, 1) double;
|
||||
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
|
||||
label (1, 1) string = "";
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, "cone")};
|
||||
end
|
||||
|
||||
obj.center = center;
|
||||
obj.radius = radius;
|
||||
obj.height = height;
|
||||
obj.tag = tag;
|
||||
obj.label = label;
|
||||
obj.tilt = tilt;
|
||||
obj.azimuth = azimuth;
|
||||
obj.center = center;
|
||||
obj.radius = radius;
|
||||
obj.height = height;
|
||||
obj.tag = tag;
|
||||
obj.label = label;
|
||||
end
|
||||
+1
-12
@@ -20,18 +20,7 @@ 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 Ref="aerpaw/scripts" Type="Relative"/>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="6402cbb5-c767-4c8b-bd7c-b2d7cf1055fc" type="Reference"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="test"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="test_rfSensor.m" type="File"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="clearRssCache.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="rfSensor.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="plotParameters.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="plotPerformance.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="halfAngle.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="computePointToPoints.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
@@ -1,2 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="sensorPerformance.m" type="File"/>
|
||||
@@ -1,6 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info>
|
||||
<Category UUID="FileClassCategory">
|
||||
<Label UUID="design"/>
|
||||
</Category>
|
||||
</Info>
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user