Merge branch 'main' into AERPAW-experiments
This commit is contained in:
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@@ -53,7 +53,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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collisionGeometry = spherical;
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collisionGeometry = collisionGeometry.initialize(params.initialPositions((((ii - 1) * 3) + 1):(ii * 3)), params.collisionRadius(ii), REGION_TYPE.COLLISION, sprintf("Agent %d collision geometry", ii));
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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), tc.plotCommsGeometry);
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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), tc.plotCommsGeometry);
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end
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% Create obstacles
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@@ -112,7 +112,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% Initialize agent
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collisionGeometry = collisionGeometry.initialize(agentPos, params.collisionRadius(ii, 1), REGION_TYPE.COLLISION, "Agent 1 Collision Region");
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agents{1} = agents{1}.initialize(agentPos, collisionGeometry, sensorModel, params.comRange(ii, 1), params.maxIter(ii), params.initialStepSize(ii), "Agent 1", tc.plotCommsGeometry);
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agents{1} = agents{1}.initialize(agentPos, collisionGeometry, sensorModel, params.comRange(ii, 1), params.maxIter(ii), params.initialStepSize(ii), 5.0, "Agent 1", tc.plotCommsGeometry);
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% Set up remaining agents in random (valid) locations
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for jj = 2:size(agents, 1)
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@@ -154,7 +154,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% Initialize agent
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collisionGeometry = collisionGeometry.initialize(agentPos, params.collisionRadius(ii, jj), REGION_TYPE.COLLISION, sprintf("Agent %d Collision Region", jj));
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agents{jj} = agents{jj}.initialize(agentPos, collisionGeometry, sensorModel, params.comRange(ii, jj), params.maxIter(ii), params.initialStepSize(ii), sprintf("Agent %d", jj), tc.plotCommsGeometry);
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agents{jj} = agents{jj}.initialize(agentPos, collisionGeometry, sensorModel, params.comRange(ii, jj), params.maxIter(ii), params.initialStepSize(ii), 5.0, sprintf("Agent %d", jj), tc.plotCommsGeometry);
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end
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% randomly shuffle agents to make the network more interesting (probably)
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+325
-50
@@ -9,8 +9,8 @@ classdef test_miSim < matlab.unittest.TestCase
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plotCommsGeometry = false; % disable plotting communications geometries
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% Sim
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maxIter = 50;
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timestep = 0.05;
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maxIter = 250;
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timestep = 0.1;
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% Domain
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domain = rectangularPrism; % domain geometry
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@@ -31,6 +31,7 @@ classdef test_miSim < matlab.unittest.TestCase
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% Agents
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initialStepSize = 0.2; % gradient ascent step size at the first iteration. Decreases linearly to 0 based on maxIter.
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initialMaxAngleStepSize = 0.1; % angular step size (degrees) for tilt/azimuth gradient ascent per timestep.
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minAgents = 3; % Minimum number of agents to be randomly generated
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maxAgents = 4; % Maximum number of agents to be randomly generated
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useDoubleIntegrator = false;
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@@ -43,6 +44,8 @@ classdef test_miSim < matlab.unittest.TestCase
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collisionRanges = NaN;
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% Sensing
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sensor = sigmoidSensor;
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% sigmoidSensor
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betaDistMin = 3;
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betaDistMax = 15;
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betaTiltMin = 3;
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@@ -51,10 +54,19 @@ classdef test_miSim < matlab.unittest.TestCase
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alphaDistMax = 3;
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alphaTiltMin = 15; % degrees
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alphaTiltMax = 30; % degrees
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sensor = sigmoidSensor;
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opticalPartitioningMin = 1e-6;
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% rfSensor
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P_TX = 1e-3; % Transmit power (Watts)
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BW = 20e6; % Bandwidth (Hz)
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f_c = 3e9; % Center frequency (Hz)
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G_RX_dBi = 3; % Receiving Antenna Gain (dBi)
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beamwidthExponent = 16;
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lossExponent = 2;
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sinrPartitioningMin = 50;
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% Communications
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useFixedTopology = false;
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optimizeSensorPointing = false;
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minCommsRange = 3; % Minimum randomly generated collision geometry size
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maxCommsRange = 5; % Maximum randomly generated collision geometry size
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commsRanges = NaN;
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@@ -173,7 +185,7 @@ classdef test_miSim < matlab.unittest.TestCase
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tc.sensor = tc.sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
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% Initialize candidate agent
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newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize);
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newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Make sure candidate agent doesn't collide with
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% domain
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@@ -227,7 +239,155 @@ classdef test_miSim < matlab.unittest.TestCase
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end
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% Initialize the simulation
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
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end
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function miSim_run_rf_sensor(tc)
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% randomly create obstacles
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nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
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tc.obstacles = cell(nGeom, 1);
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% Iterate over obstacles to initialize
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for ii = 1:size(tc.obstacles, 1)
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badCandidate = true;
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while badCandidate
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% Instantiate a rectangular prism obstacle inside the domain
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tc.obstacles{ii} = rectangularPrism;
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tc.obstacles{ii} = tc.obstacles{ii}.initializeRandom(REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii), tc.minObstacleSize, tc.maxObstacleSize, tc.domain, tc.minAlt);
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% Check if the obstacle collides with an existing obstacle
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if ~tc.obstacleCollisionCheck(tc.obstacles(1:(ii - 1)), tc.obstacles{ii})
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badCandidate = false;
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end
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end
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end
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% Add agents individually, ensuring that each addition does not
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% invalidate the initialization setup
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for ii = 1:size(tc.agents, 1)
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initInvalid = true;
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while initInvalid
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candidatePos = [tc.domain.objective.groundPos, 0];
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% Generate a random position for the agent based on
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% existing agent positions
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if ii == 1
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while agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
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candidatePos = tc.domain.random();
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candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, tc.minAlt + rand * (tc.alphaDistMax * (1.1) - 0.5)]); % place agents at decent altitudes for sensing
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end
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else
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candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.commsRanges(ii)/sqrt(2));
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candidatePos(3) = min([tc.domain.maxCorner(3) * 0.95, tc.minAlt + rand * (tc.alphaDistMax * (1.1) - 0.5)]); % place agents at decent altitudes for sensing
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end
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% Make sure that the candidate position is within the
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% domain
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if ~tc.domain.contains(candidatePos)
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continue;
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end
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% Make sure that the candidate position does not crowd
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% the sensing objective and create boring scenarios
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if agentsCrowdObjective(tc.domain.objective, candidatePos, mean(tc.domain.dimensions) / 2)
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continue;
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end
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% Make sure that there exist unobstructed lines of sight at
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% appropriate ranges to form a connected communications
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% graph between the agents
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connections = false(1, ii - 1);
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for jj = 1:(ii - 1)
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if norm(tc.agents{jj}.pos - candidatePos) <= min(tc.commsRanges([ii, jj]))
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% Check new agent position against all existing
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% agent positions for communications range
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connections(jj) = true;
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for kk = 1:size(tc.obstacles, 1)
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if tc.obstacles{kk}.containsLine(tc.agents{jj}.pos, candidatePos)
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connections(jj) = false;
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end
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end
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end
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end
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% New agent must be connected to an existing agent to
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% be valid
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if ii ~= 1 && ~any(connections)
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continue;
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end
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% Initialize candidate agent collision geometry
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% candidateGeometry = rectangularPrism;
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% candidateGeometry = candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii) * ones(1, 3); candidatePos + tc.collisionRanges(ii) * ones(1, 3)], REGION_TYPE.COLLISION);
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candidateGeometry = spherical;
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candidateGeometry = candidateGeometry.initialize(candidatePos, tc.collisionRanges(ii), REGION_TYPE.COLLISION);
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% Initialize candidate agent sensor model
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tc.sensor = rfSensor;
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tilt = 0; azimuth = 0;
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tc.sensor = tc.sensor.initialize(tc.P_TX * 1 + rand * 4, tc.BW, tc.f_c, tc.G_RX_dBi, tc.beamwidthExponent + randi(100), tilt, azimuth, tc.lossExponent);
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% Initialize candidate agent
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newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Make sure candidate agent doesn't collide with
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% domain
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violation = false;
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for jj = 1:size(newAgent.collisionGeometry.vertices, 1)
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% Check if collision geometry exits domain
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if ~tc.domain.contains(newAgent.collisionGeometry.vertices(jj, 1:3))
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violation = true;
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break;
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end
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end
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if violation
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continue;
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end
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% Make sure candidate doesn't collide with obstacles
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violation = false;
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for kk = 1:size(tc.obstacles, 1)
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if geometryIntersects(tc.obstacles{kk}, newAgent.collisionGeometry)
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violation = true;
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break;
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end
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end
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if violation
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continue;
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end
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% Make sure candidate doesn't collide with existing
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% agents
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violation = false;
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for kk = 1:(ii - 1)
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if geometryIntersects(tc.agents{kk}.collisionGeometry, newAgent.collisionGeometry)
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violation = true;
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break;
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end
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end
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% Make sure candidate clears domain floor
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if newAgent.pos(3) - newAgent.collisionGeometry.radius <= tc.minAlt
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violation = true;
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end
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if violation
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continue;
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end
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% Candidate agent is valid, store to pass in to sim
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initInvalid = false;
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tc.agents{ii} = newAgent;
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end
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end
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% Initialize the simulation
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tc.optimizeSensorPointing = true;
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
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% Write out initialization state
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tc.testClass.writeInits();
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% Run simulation loop
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tc.testClass = tc.testClass.run();
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end
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function miSim_run(tc)
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% randomly create obstacles
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@@ -312,7 +472,7 @@ classdef test_miSim < matlab.unittest.TestCase
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tc.sensor = tc.sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
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% Initialize candidate agent
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newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize);
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newAgent = tc.agents{ii}.initialize(candidatePos, candidateGeometry, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Make sure candidate agent doesn't collide with
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% domain
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@@ -366,7 +526,7 @@ classdef test_miSim < matlab.unittest.TestCase
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end
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% Initialize the simulation
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
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% Write out initialization state
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tc.testClass.writeInits();
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@@ -392,15 +552,15 @@ classdef test_miSim < matlab.unittest.TestCase
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% Initialize agents
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tc.commsRanges = 3 * d * ones(size(tc.agents));
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tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
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tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [d, 0, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
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tc.agents{3} = tc.agents{3}.initialize(tc.domain.center - [0, d, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize);
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tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [d, 0, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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tc.agents{3} = tc.agents{3}.initialize(tc.domain.center - [0, d, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Initialize the simulation
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tc.obstacles = cell(0, 1);
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tc.makePlots = false;
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tc.makeVideo = false;
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
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centerIdx = floor(size(tc.testClass.partitioning, 1) / 2);
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tc.verifyEqual(tc.testClass.partitioning(centerIdx, centerIdx:(centerIdx + 2)), [2, 3, 1]); % all three near center
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@@ -419,13 +579,13 @@ classdef test_miSim < matlab.unittest.TestCase
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tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3);
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% Initialize agents
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tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
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tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Initialize the simulation
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tc.obstacles = cell(0, 1);
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tc.makePlots = false;
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tc.makeVideo = false;
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
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close(tc.testClass.fPerf);
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tc.verifyEqual(unique(tc.testClass.partitioning), [0; 1]);
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@@ -437,7 +597,7 @@ classdef test_miSim < matlab.unittest.TestCase
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tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
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% make basic sensing objective
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tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [7, 6]);
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tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [7, 6]);
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% Initialize agent collision geometry
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tc.agents = {agent};
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@@ -449,14 +609,129 @@ classdef test_miSim < matlab.unittest.TestCase
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% Initialize agents
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tc.maxIter = 75;
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tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
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tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
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% Initialize the simulation
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tc.obstacles = cell(0, 1);
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tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();end
|
||||
tc.testClass = tc.testClass.run();
|
||||
end
|
||||
function test_single_agent_gradient_ascent_tilted(tc)
|
||||
% make basic domain
|
||||
tc.minDimension = 10; % domain size
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [7, 6]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent};
|
||||
geometry1 = spherical;
|
||||
geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
|
||||
|
||||
% Initialize agent sensor model with fixed parameters
|
||||
tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3, 25, 155);
|
||||
|
||||
% Initialize agents
|
||||
tc.maxIter = 75;
|
||||
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.obstacles = cell(0, 1);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();
|
||||
end
|
||||
function test_single_agent_gradient_ascent_tilted_RF_sensor(tc)
|
||||
% make basic domain
|
||||
tc.minDimension = 10; % domain size
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.sinrPartitioningMin, [7, 6]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent};
|
||||
geometry1 = spherical;
|
||||
geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
|
||||
|
||||
tc.sensor = rfSensor;
|
||||
tc.sensor = tc.sensor.initialize(tc.P_TX, tc.BW, tc.f_c, tc.G_RX_dBi, tc.beamwidthExponent, 45, 45, tc.lossExponent);
|
||||
|
||||
% Initialize agents
|
||||
tc.maxIter = 75;
|
||||
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.obstacles = cell(0, 1);
|
||||
tc.minAlt = 0.5;
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();
|
||||
end
|
||||
function test_single_agent_gradient_ascent_sensor_pointing(tc)
|
||||
% make basic domain
|
||||
tc.minDimension = 10; % domain size
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [7, 6]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent};
|
||||
geometry1 = spherical;
|
||||
geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
|
||||
|
||||
% Initialize agent sensor model with fixed parameters
|
||||
tc.sensor = tc.sensor.initialize(tc.minDimension / 2, 3, 20, 3);
|
||||
|
||||
% Initialize agents
|
||||
tc.maxIter = 75;
|
||||
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.optimizeSensorPointing = true;
|
||||
tc.obstacles = cell(0, 1);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();
|
||||
end
|
||||
function test_single_agent_gradient_ascent_rf_sensor_pointing(tc)
|
||||
% make basic domain
|
||||
tc.minDimension = 10; % domain size
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([7, 6]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.sinrPartitioningMin, [7, 6]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent};
|
||||
geometry1 = spherical;
|
||||
geometry1 = geometry1.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], tc.collisionRanges(1), REGION_TYPE.COLLISION);
|
||||
|
||||
% Initialize agent sensor model
|
||||
|
||||
tc.sensor = rfSensor;
|
||||
tc.sensor = tc.sensor.initialize(tc.P_TX, tc.BW, tc.f_c, tc.G_RX_dBi, tc.beamwidthExponent, 0, 0, tc.lossExponent);
|
||||
|
||||
% Initialize agents
|
||||
tc.maxIter = 75;
|
||||
tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2)-tc.domain.dimensions(1)/4, 3], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.optimizeSensorPointing = true;
|
||||
tc.obstacles = cell(0, 1);
|
||||
tc.minAlt = 0.5;
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();
|
||||
end
|
||||
function test_collision_avoidance(tc)
|
||||
% No obstacles
|
||||
% Fixed agent initial conditions
|
||||
@@ -466,7 +741,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [3, 7]);
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([3, 7]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [3, 7]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent; agent};
|
||||
@@ -483,12 +758,12 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Initialize agents
|
||||
tc.maxIter = 25;
|
||||
tc.commsRanges = 5 * ones(size(tc.agents));
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.obstacles = cell(0, 1);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass.run();
|
||||
@@ -504,7 +779,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5.2195]);
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5.2195]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [8, 5.2195]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent; agent;};
|
||||
@@ -530,11 +805,11 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
|
||||
% Initialize agents
|
||||
tc.commsRanges = (2 * tc.collisionRanges(1) + obstacleLength) * 0.9 * ones(size(tc.agents)); % defined such that they cannot go around the obstacle on both sides
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, tc.collisionRanges(1) * 1.1 - yOffset, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, tc.collisionRanges(2) *1.1 + yOffset, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - d + [0, tc.collisionRanges(1) * 1.1 - yOffset, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d - [0, tc.collisionRanges(2) *1.1 + yOffset, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass.run();
|
||||
@@ -570,11 +845,11 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Initialize agents
|
||||
tc.maxIter = 50;
|
||||
tc.commsRanges = 4 * ones(size(tc.agents)); % defined such that they cannot reach their objective without breaking connectivity
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + d, geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - d, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Run the simulation
|
||||
tc.testClass = tc.testClass.run();
|
||||
@@ -588,7 +863,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [8, 5]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent; agent;};
|
||||
@@ -605,8 +880,8 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Initialize agents
|
||||
tc.maxIter = 125;
|
||||
tc.commsRanges = 5 * ones(size(tc.agents));
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center - [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [0, d, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize obstacles
|
||||
obstacleLength = 1.5;
|
||||
@@ -617,7 +892,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.minAlt = 0;
|
||||
tc.makePlots = false;
|
||||
tc.makeVideo = false;
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Communications link should be established
|
||||
tc.assertEqual(tc.testClass.adjacency, logical(true(2)));
|
||||
@@ -633,7 +908,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3);tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [8, 5]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent; agent; agent; agent; agent;};
|
||||
@@ -652,17 +927,17 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Initialize agents
|
||||
tc.maxIter = 125;
|
||||
tc.commsRanges = ones(size(tc.agents));
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], geometry4, tc.sensor, tc.commsRanges(4), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], geometry5, tc.sensor, tc.commsRanges(5), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center, geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [-d, d, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [-2*d, d, 0], geometry4, tc.sensor, tc.commsRanges(4), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, d, 0], geometry5, tc.sensor, tc.commsRanges(5), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.minAlt = 0;
|
||||
tc.makePlots = false;
|
||||
tc.makeVideo = false;
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Constraint adjacency matrix defined by LNA should be as follows
|
||||
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
|
||||
@@ -683,7 +958,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.domain = tc.domain.initialize([zeros(1, 3); tc.minDimension* ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
|
||||
|
||||
% make basic sensing objective
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, 1e-6, [8, 5]);
|
||||
tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([8, 5]), tc.domain, tc.discretizationStep, tc.protectedRange, tc.opticalPartitioningMin, [8, 5]);
|
||||
|
||||
% Initialize agent collision geometry
|
||||
tc.agents = {agent; agent; agent; agent; agent; agent; agent;};
|
||||
@@ -704,19 +979,19 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Initialize agents
|
||||
tc.maxIter = 125;
|
||||
tc.commsRanges = d * ones(size(tc.agents));
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], geometry4, tc.sensor, tc.commsRanges(4), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], geometry5, tc.sensor, tc.commsRanges(5), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, geometry6, tc.sensor, tc.commsRanges(6), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], geometry7, tc.sensor, tc.commsRanges(7), tc.maxIter, tc.initialStepSize);
|
||||
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [-0.9 * d/sqrt(2), 0.9 * d/sqrt(2), 0], geometry1, tc.sensor, tc.commsRanges(1), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + [-0.5 * d, 0.25 * d, 0], geometry2, tc.sensor, tc.commsRanges(2), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + [0.9 * d, 0, 0], geometry3, tc.sensor, tc.commsRanges(3), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{4} = tc.agents{4}.initialize(tc.domain.center + [0.9 * d/sqrt(2), -0.9 * d/sqrt(2), 0], geometry4, tc.sensor, tc.commsRanges(4), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{5} = tc.agents{5}.initialize(tc.domain.center + [0, 0.9 * d, 0], geometry5, tc.sensor, tc.commsRanges(5), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{6} = tc.agents{6}.initialize(tc.domain.center, geometry6, tc.sensor, tc.commsRanges(6), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
tc.agents{7} = tc.agents{7}.initialize(tc.domain.center + [d/2, d/2, 0], geometry7, tc.sensor, tc.commsRanges(7), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Initialize the simulation
|
||||
tc.minAlt = 0;
|
||||
tc.makePlots = false;
|
||||
tc.makeVideo = false;
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, tc.makePlots, tc.makeVideo, tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Constraint adjacency matrix defined by LNA should be as follows
|
||||
tc.assertEqual(tc.testClass.constraintAdjacencyMatrix, logical( ...
|
||||
@@ -796,7 +1071,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), ...
|
||||
tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
|
||||
newAgent = agent;
|
||||
newAgent = newAgent.initialize(candidatePos, geom, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize);
|
||||
newAgent = newAgent.initialize(candidatePos, geom, tc.sensor, tc.commsRanges(ii), tc.maxIter, tc.initialStepSize, tc.initialMaxAngleStepSize);
|
||||
|
||||
% Domain / obstacle / agent collision checks
|
||||
violation = false;
|
||||
@@ -831,7 +1106,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
sim1 = miSim;
|
||||
sim1 = sim1.initialize(tc.domain, tc.agents, tc.barrierGain, tc.barrierExponent, ...
|
||||
tc.minAlt, tc.timestep, tc.maxIter, tc.obstacles, false, false, ...
|
||||
tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology);
|
||||
tc.useDoubleIntegrator, tc.dampingCoeff, tc.useFixedTopology, tc.optimizeSensorPointing);
|
||||
|
||||
% Write inits and build file path
|
||||
sim1.writeInits();
|
||||
|
||||
@@ -0,0 +1,170 @@
|
||||
classdef test_rfSensor < matlab.unittest.TestCase
|
||||
properties (Access = private)
|
||||
% System under test
|
||||
testClass = sigmoidSensor;
|
||||
end
|
||||
|
||||
methods (TestMethodSetup)
|
||||
function tc = setup(tc)
|
||||
% Reinitialize sensor with random parameters
|
||||
tc.testClass = rfSensor;
|
||||
end
|
||||
end
|
||||
|
||||
methods (Test)
|
||||
function plot_RSS(tc)
|
||||
% Plot sensor performance with no sources of interference
|
||||
P_TX = 1e-3; % Transmit power (Watts)
|
||||
BW = 20e6; % Bandwidth (Hz)
|
||||
f_c = 2e9; % Center frequency (Hz)
|
||||
G_RX_dBi = 3; % Receiving Antenna Gain (dBi)
|
||||
beamwidthExponent = 6;
|
||||
lossExponent = 2;
|
||||
|
||||
tc.testClass = tc.testClass.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 0, 0, lossExponent);
|
||||
|
||||
tc.testClass.plotParameters();
|
||||
end
|
||||
function plot_SNR(tc)
|
||||
% Plot sensor performance with no sources of interference
|
||||
P_TX = 1e-3; % Transmit power (Watts)
|
||||
BW = 20e6; % Bandwidth (Hz)
|
||||
f_c = 2e9; % Center frequency (Hz)
|
||||
G_RX_dBi = 3; % Receiving Antenna Gain (dBi)
|
||||
beamwidthExponent = 6;
|
||||
lossExponent = 2;
|
||||
|
||||
tc.testClass = tc.testClass.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 30, 135, lossExponent);
|
||||
|
||||
altitude = 30;
|
||||
|
||||
% Boresight azimuth=135° (between +X at 90° and -Y at 180°) → hotspot at +X,-Y.
|
||||
% SNR at (5,-5) should be higher than at (5,+5).
|
||||
agentPos = [0, 0, altitude];
|
||||
[~, snrA] = tc.testClass.sensorPerformance(agentPos, [5, -5, 0]);
|
||||
% tc.testClass = tc.testClass.clearRssCache();
|
||||
[~, snrB] = tc.testClass.sensorPerformance(agentPos, [5, 5, 0]);
|
||||
tc.assertGreaterThan(snrA, snrB, "SNR should be higher toward boresight (+X,-Y) than away from it (+X,+Y)");
|
||||
|
||||
tc.testClass.plotPerformance(altitude);
|
||||
end
|
||||
function plot_SINR_one_interferer(tc)
|
||||
% Plot sensor performance with no sources of interference
|
||||
P_TX = 1e-3; % Transmit power (Watts)
|
||||
BW = 20e6; % Bandwidth (Hz)
|
||||
f_c = 2e9; % Center frequency (Hz)
|
||||
G_RX_dBi = 3; % Receiving Antenna Gain (dBi)
|
||||
beamwidthExponent = 6;
|
||||
lossExponent = 2;
|
||||
|
||||
tc.testClass = tc.testClass.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 0, 0, lossExponent);
|
||||
|
||||
altitude = 30;
|
||||
otherSensorsPos = [6, -4, -1]; % relative to main sensor
|
||||
otherSensors = cell(1, 1);
|
||||
otherSensors{1} = tc.testClass; % One interfering sensor, identical to the main sensor
|
||||
|
||||
tc.testClass.plotPerformance(altitude, otherSensorsPos, otherSensors);
|
||||
end
|
||||
|
||||
function plot_SINR_heterogenous_interferers(tc)
|
||||
% Plot sensor performance with no sources of interference
|
||||
P_TX = 1e-3; % Transmit power (Watts)
|
||||
BW = 20e6; % Bandwidth (Hz)
|
||||
f_c = 2e9; % Center frequency (Hz)
|
||||
G_RX_dBi = 3; % Receiving Antenna Gain (dBi)
|
||||
beamwidthExponent = 6;
|
||||
lossExponent = 2;
|
||||
|
||||
tc.testClass = tc.testClass.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 0, 0, lossExponent);
|
||||
|
||||
altitude = 30;
|
||||
otherSensorsPos = [6, -4, -1; -2, 6, 0]; % relative to main sensor
|
||||
otherSensors = cell(2, 1);
|
||||
otherSensors{1} = rfSensor; % two heterogenous interfering sensors
|
||||
otherSensors{2} = rfSensor;
|
||||
|
||||
% Must use same center frequency and bandwidth for interference sources
|
||||
otherSensors{1} = otherSensors{1}.initialize(10 * P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 0, 0, lossExponent);
|
||||
otherSensors{2} = otherSensors{2}.initialize(10 * P_TX, BW, f_c, G_RX_dBi, beamwidthExponent, 0, 0, lossExponent);
|
||||
|
||||
tc.testClass.plotPerformance(altitude, otherSensorsPos, otherSensors);
|
||||
end
|
||||
function plot_SINR_heterogenous_interferers_efficiently(tc)
|
||||
P_TX = 1e-3;
|
||||
BW = 20e6;
|
||||
f_c = 2e9;
|
||||
G_RX_dBi = 3;
|
||||
altitude = 30;
|
||||
beamwidthExponent = [6, 4, 10];
|
||||
lossExponent = 2;
|
||||
|
||||
sensor1 = rfSensor;
|
||||
sensor1 = sensor1.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(1), 15, 45, lossExponent);
|
||||
sensor2 = rfSensor;
|
||||
sensor2 = sensor2.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(2), 10, 150, lossExponent);
|
||||
sensor3 = rfSensor;
|
||||
sensor3 = sensor3.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(3), 20, 200, lossExponent);
|
||||
|
||||
pos1 = [0, 0, altitude];
|
||||
pos2 = [6, -4, altitude - 1];
|
||||
pos3 = [-2, 6, altitude];
|
||||
|
||||
% Build a shared target grid
|
||||
distances = -15:0.25:15;
|
||||
[Xg, Yg] = meshgrid(distances, distances);
|
||||
targetPos = [Xg(:), Yg(:), zeros(numel(Xg), 1)];
|
||||
|
||||
% Call 1: cache empty, does all computations for this timestep
|
||||
[~, ~, sensor1, others] = sensor1.sensorPerformance(pos1, targetPos, [pos2; pos3], {sensor2; sensor3});
|
||||
sensor2 = others{1};
|
||||
sensor3 = others{2};
|
||||
|
||||
% Calls 2 and 3 use cached data
|
||||
[~, ~, sensor2, others] = sensor2.sensorPerformance(pos2, targetPos, [pos1; pos3], {sensor1; sensor3});
|
||||
sensor1 = others{1};
|
||||
sensor3 = others{2};
|
||||
|
||||
[~, ~, sensor3, ~] = sensor3.sensorPerformance(pos3, targetPos, [pos1; pos2], {sensor1; sensor2});
|
||||
|
||||
% All caches should be populated after the three calls
|
||||
tc.assertNotEmpty(sensor1.rssCache);
|
||||
tc.assertNotEmpty(sensor2.rssCache);
|
||||
tc.assertNotEmpty(sensor3.rssCache);
|
||||
|
||||
% Plot SINR from each UAV's perspective.
|
||||
% otherSensorsPos for plotPerformance: XY = offset from calling sensor, Z = absolute_alt - calling_alt.
|
||||
% This is exactly posOther - posSelf for each row.
|
||||
sensor1.plotPerformance(pos1(3), [pos2 - pos1; pos3 - pos1], {sensor2; sensor3});
|
||||
sensor2.plotPerformance(pos2(3), [pos1 - pos2; pos3 - pos2], {sensor1; sensor3});
|
||||
sensor3.plotPerformance(pos3(3), [pos1 - pos3; pos2 - pos3], {sensor1; sensor2});
|
||||
end
|
||||
function plot_SINR_heterogenous_interferers_3d(tc)
|
||||
P_TX = 1e-3;
|
||||
BW = 20e6;
|
||||
f_c = 2e9;
|
||||
G_RX_dBi = 3;
|
||||
altitude = 30;
|
||||
beamwidthExponent = [50, 20, 200];
|
||||
lossExponent = 2;
|
||||
|
||||
sensor1 = rfSensor;
|
||||
sensor1 = sensor1.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(1), 15, 45, lossExponent);
|
||||
sensor2 = rfSensor;
|
||||
sensor2 = sensor2.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(2), 10, 150, lossExponent);
|
||||
sensor3 = rfSensor;
|
||||
sensor3 = sensor3.initialize(P_TX, BW, f_c, G_RX_dBi, beamwidthExponent(3), 20, 200, lossExponent);
|
||||
|
||||
pos1 = [0, 0, altitude];
|
||||
pos2 = [6, -4, altitude - 5];
|
||||
pos3 = [-2, 6, altitude + 10];
|
||||
|
||||
% Plot SINR from each UAV's perspective.
|
||||
% otherSensorsPos for plotPerformance: XY = offset from calling sensor, Z = absolute_alt - calling_alt.
|
||||
% This is exactly posOther - posSelf for each row.
|
||||
sensor1.plot(pos1(3), [pos2 - pos1; pos3 - pos1], {sensor2; sensor3});
|
||||
sensor2.plot(pos2(3), [pos1 - pos2; pos3 - pos2], {sensor1; sensor3});
|
||||
sensor3.plot(pos3(3), [pos1 - pos3; pos2 - pos3], {sensor1; sensor2});
|
||||
end
|
||||
end
|
||||
end
|
||||
Reference in New Issue
Block a user