416 lines
20 KiB
Matlab
416 lines
20 KiB
Matlab
classdef test_miSim < matlab.unittest.TestCase
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properties (Access = private)
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% System under test
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testClass = miSim;
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% Sim
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maxIter = 250;
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timestep = 0.05
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partitoningFreq = 5;
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% Domain
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domain = rectangularPrism; % domain geometry
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minDimension = 10;
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% Obstacles
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minNumObstacles = 1; % Minimum number of obstacles to be randomly generated
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maxNumObstacles = 3; % Maximum number of obstacles to be randomly generated
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minObstacleSize = 1; % Minimum size of a randomly generated obstacle
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maxObstacleSize = 6; % Maximum size of a randomly generated obstacle
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obstacles = cell(1, 0);
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% Objective
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discretizationStep = 0.01; % Step at which the objective function is solved in X and Y space
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protectedRange = 1; % Minimum distance between the sensing objective and the edge of the domain
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objective = sensingObjective;
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% Agents
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minAgents = 2; % 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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sensingLength = 0.05; % length parameter used by sensing function
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agents = cell(0, 1);
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% Collision
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minCollisionRange = 0.1; % Minimum randomly generated collision geometry size
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maxCollisionRange = 0.5; % Maximum randomly generated collision geometry size
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collisionRanges = NaN;
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% Sensing
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betaDistMin = 3;
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betaDistMax = 15;
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betaTiltMin = 3;
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betaTiltMax = 15;
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alphaDistMin = 2.5;
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alphaDistMax = 3;
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alphaTiltMin = deg2rad(15);
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alphaTiltMax = deg2rad(30);
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% Communications
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comRange = 8; % Maximum range between agents that forms a communications link
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end
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% Setup for each test
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methods (TestMethodSetup)
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% Generate a random domain
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function tc = setDomain(tc)
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% random integer-dimensioned cubic domain
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tc.domain = tc.domain.initializeRandom(REGION_TYPE.DOMAIN, "Domain", tc.minDimension);
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% Random bivariate normal PDF objective
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tc.domain.objective = tc.domain.objective.initializeRandomMvnpdf(tc.domain, tc.discretizationStep, tc.protectedRange);
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end
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% Instantiate agents
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function tc = setAgents(tc)
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% Agents will be initialized under different parameters in individual test cases
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% Instantiate a random number of agents according to parameters
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for ii = 1:randi([tc.minAgents, tc.maxAgents])
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tc.agents{ii, 1} = agent;
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end
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% Define random collision ranges for each agent
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tc.collisionRanges = tc.minCollisionRange + rand(size(tc.agents, 1), 1) * (tc.maxCollisionRange - tc.minCollisionRange);
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end
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end
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methods (Test)
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% Test methods
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function misim_initialization(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);
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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) = 2 + rand * 2; % 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.comRange/sqrt(2));
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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) <= tc.comRange
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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, sprintf("Agent %d collision volume", ii));
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% Initialize candidate agent sensor model
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sensor = sigmoidSensor;
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sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
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% Initialize candidate agent
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newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, tc.comRange, ii, sprintf("Agent %d", ii));
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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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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.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles);
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end
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function misim_run(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);
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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, 0.5 + 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.comRange/sqrt(2));
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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) <= tc.comRange
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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, sprintf("Agent %d collision volume", ii));
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% Initialize candidate agent sensor model
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sensor = sigmoidSensor;
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sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
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% Initialize candidate agent
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newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, tc.comRange, ii, sprintf("Agent %d", ii));
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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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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.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles);
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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 test_basic_partitioning(tc)
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% place agents a fixed distance +/- X from the domain's center
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d = 1;
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% make basic domain
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tc.domain = tc.domain.initialize([zeros(1, 3); 10 * 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(@(x, y) mvnpdf([x(:), y(:)], tc.domain.center(1:2)), tc.domain, tc.discretizationStep, tc.protectedRange);
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% Initialize agent collision geometry
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geometry1 = rectangularPrism;
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geometry2 = geometry1;
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geometry1 = geometry1.initialize([tc.domain.center + [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 1));
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geometry2 = geometry2.initialize([tc.domain.center - [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center - [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 2));
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% Initialize agent sensor model
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sensor = sigmoidSensor;
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% Homogeneous sensor model parameters
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sensor = sensor.initialize(2.5, 3, NaN, NaN, deg2rad(15), 3);
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f = sensor.plotParameters();
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% Heterogeneous sensor model parameters
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% sensor = sensor.initialize(tc.alphaDistMin + rand * (tc.alphaDistMax - tc.alphaDistMin), tc.betaDistMin + rand * (tc.betaDistMax - tc.betaDistMin), NaN, NaN, tc.alphaTiltMin + rand * (tc.alphaTiltMax - tc.alphaTiltMin), tc.betaTiltMin + rand * (tc.betaTiltMax - tc.betaTiltMin));
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% Initialize agents
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tc.agents = {agent; agent};
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tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, @gradientAscent, 3*d, 1, sprintf("Agent %d", 1));
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tc.agents{2} = tc.agents{2}.initialize(tc.domain.center - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, @gradientAscent, 3*d, 2, sprintf("Agent %d", 2));
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% Optional third agent along the +Y axis
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geometry3 = rectangularPrism;
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geometry3 = geometry3.initialize([tc.domain.center - [0, d, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center - [0, d, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 3));
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tc.agents{3} = agent;
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tc.agents{3} = tc.agents{3}.initialize(tc.domain.center - [0, d, 0], zeros(1, 3), 0, 0, geometry3, sensor, @gradientAscent, 3*d, 3, sprintf("Agent %d", 3));
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% Initialize the simulation
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tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
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end
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function test_annular_partition(tc)
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% make basic domain
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tc.domain = tc.domain.initialize([zeros(1, 3); 10 * 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(@(x, y) mvnpdf([x(:), y(:)], tc.domain.center(1:2)), tc.domain, tc.discretizationStep, tc.protectedRange);
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% Initialize agent collision geometry
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geometry1 = rectangularPrism;
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geometry1 = geometry1.initialize([[tc.domain.center(1:2), 3] - tc.collisionRanges(1) * ones(1, 3); [tc.domain.center(1:2), 3] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 1));
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% Initialize agent sensor model
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sensor = sigmoidSensor;
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% Homogeneous sensor model parameters
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sensor = sensor.initialize(2.5666, 5.0807, NaN, NaN, 0.3641, 13);
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f = sensor.plotParameters();
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% Initialize agents
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tc.agents = {agent};
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tc.agents{1} = tc.agents{1}.initialize([tc.domain.center(1:2), 3], zeros(1,3), 0, 0, geometry1, sensor, @gradientAscent, 3, 1, sprintf("Agent %d", 1));
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% Initialize the simulation
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tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
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end
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end
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methods
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function c = obstacleCollisionCheck(~, obstacles, obstacle)
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% Check if the obstacle intersects with any other obstacles
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c = false;
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for ii = 1:size(obstacles, 1)
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if geometryIntersects(obstacles{ii}, obstacle)
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c = true;
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end
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end
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end
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end
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end |