added random obstacles
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@@ -3,10 +3,9 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% System under test
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testClass = miSim;
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domain = rectangularPrism;
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obstacles = cell(1, 0);
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% RNG control
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seed = 1234567890;
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seed = 1;
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%% Diagnostic Parameters
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% No effect on simulation dynamics
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@@ -41,7 +40,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% Read file
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csv = readtable(csvPath, "TextType", "String", "NumHeaderLines", 0, "VariableNamingRule", "Preserve");
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csv.Properties.VariableNames = ["timestep", "maxIter", "minAlt", "discretizationStep", "sensorPerformanceMinimum", "initialStepSize", "barrierGain", "barrierExponent", "numObstacles", "numAgents", "collisionRadius", "comRange", "alphaDist", "betaDist", "alphaTilt", "betaTilt"];
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csv.Properties.VariableNames = ["timestep", "maxIter", "minAlt", "discretizationStep", "protectedRange", "sensorPerformanceMinimum", "initialStepSize", "barrierGain", "barrierExponent", "numObstacles", "numAgents", "collisionRadius", "comRange", "alphaDist", "betaDist", "alphaTilt", "betaTilt"];
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for ii = 1:size(csv.Properties.VariableNames, 2)
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csv.(csv.Properties.VariableNames{ii}) = cell2mat(cellfun(@(x) str2num(x), csv.(csv.Properties.VariableNames{ii}), "UniformOutput", false));
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@@ -49,7 +48,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% Put params into standard structure
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params = struct("timestep", csv.timestep, "maxIter", csv.maxIter, "minAlt", csv.minAlt, "discretizationStep", csv.discretizationStep, ...
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"sensorPerformanceMinimum", csv.sensorPerformanceMinimum, "initialStepSize", csv.initialStepSize, ...
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"protectedRange", csv.protectedRange, "sensorPerformanceMinimum", csv.sensorPerformanceMinimum, "initialStepSize", csv.initialStepSize, ...
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"barrierGain", csv.barrierGain, "barrierExponent", csv.barrierExponent, "numObstacles", csv.numObstacles,...
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"numAgents", csv.numAgents, "collisionRadius", csv.collisionRadius, "comRange", csv.comRange, "alphaDist", csv.alphaDist, "betaDist", csv.betaDist, "alphaTilt", csv.alphaTilt, "betaTilt", csv.betaTilt);
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end
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@@ -70,7 +69,7 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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for ii = 1:size(params.timestep, 1)
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% Set up square domain
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tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
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tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, params.discretizationStep(ii), tc.protectedRange, params.sensorPerformanceMinimum(ii));
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tc.domain.objective = tc.domain.objective.initialize(objectiveFunctionWrapper([.75 * l, 0.75 * l]), tc.domain, params.discretizationStep(ii), params.protectedRange(ii), params.sensorPerformanceMinimum(ii));
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% Initialize agents
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agents = cell(params.numAgents(ii), 1);
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@@ -105,29 +104,27 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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retry = true;
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while retry
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agentPos = agents{baseAgentIdx}.commsGeometry.random();
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retry = false;
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% Check that the agent's greatest sensor
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% performance clears the threshold for partitioning
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if sensorModel.sensorPerformance(agentPos, [agentPos(1:2), 0]) < params.sensorPerformanceMinimum(ii)
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retry = true;
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continue;
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end
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% Check that candidate position is well inside the domain
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bounds = [params.collisionRadius(ii, jj) * ones(1, 2), max([params.collisionRadius(ii, jj), params.minAlt(ii)]); l / 2 * ones(1, 2), l - params.collisionRadius(ii, jj)];
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if ~isequal(agentPos < bounds, [false, false, false; true, true, true])
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if ~retry && ~isequal(agentPos < bounds, [false, false, false; true, true, true])
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retry = true;
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continue;
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end
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% Check that candidate position does not collide with existing agents
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for kk = 1:(jj - 1)
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if norm(agents{kk}.pos - agentPos, 2) < agents{kk}.collisionGeometry.radius + params.collisionRadius(ii, jj)
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if ~retry && norm(agents{kk}.pos - agentPos, 2) < agents{kk}.collisionGeometry.radius + params.collisionRadius(ii, jj)
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retry = true;
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continue;
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break;
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end
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end
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retry = false;
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end
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% Initialize agent
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@@ -135,9 +132,66 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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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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end
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% randomly shuffle agents to make the network more interesting (probably)
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agents = agents(randperm(numel(agents)));
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% Set up obstacles
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obstacles = cell(params.numObstacles(ii), 1);
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[obstacles{:}] = deal(rectangularPrism);
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% Define ranges to permit obstacles (relies on certain
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% assumptions about agent and objective placement)
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bounds = [max(cell2mat(cellfun(@(x) x.pos(1:2), agents, "UniformOutput", false))) + max(cellfun(@(x) x.collisionGeometry.radius, agents)); ...
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tc.domain.objective.groundPos - tc.domain.objective.protectedRange];
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for jj = 1:size(obstacles, 1)
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% randomly place obstacles in at least the X or Y or X
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% and Y range defined by the objective region and the
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% agents initial region
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retry = true;
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while retry
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retry = false;
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% candidate corners for obstacle
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corners = [sort(tc.domain.maxCorner(1, 1:2) .* rand(2), 1, "ascend"), [params.minAlt(ii); params.minAlt(ii) + rand * (tc.domain.maxCorner(3) - params.minAlt(ii))]];
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% Check X falls into bucket in at least one vertex
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if ~retry && ~(any(corners(:, 1) > bounds(1, 1) & corners(:, 1) < bounds(2, 1)) || any(corners(:, 2) > bounds(1, 2) & corners(:, 2) < bounds(2, 2)))
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retry = true;
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end
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% Initialize obstacle using proposed coordinates
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if ~retry
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obstacles{jj} = obstacles{jj}.initialize(corners, REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", jj));
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end
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% Make sure the obstacle doesn't crowd the objective
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if ~retry && obstacles{jj}.distance([tc.domain.objective.groundPos, params.minAlt(ii)]) <= tc.domain.objective.protectedRange
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retry = true;
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end
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% Check if the obstacle collides with an existing obstacle
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if ~retry && jj > 1 && tc.obstacleCollisionCheck(obstacles(1:(jj - 1)), obstacles{jj})
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retry = true;
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end
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% Check if the obstacle collides with an agent
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if ~retry
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AO_collisions = cellfun(@(a) cellfun(@(o) o.contains(a.pos), obstacles), agents, "UniformOutput", false);
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if any(vertcat(AO_collisions{:}))
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retry = true;
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end
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end
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if retry
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continue;
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end
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end
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end
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% Set up simulation
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agents = agents(randperm(numel(agents))); % randomly shuffle agents to make the network more interesting (probably)
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tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain(ii), params.barrierExponent(ii), params.minAlt(ii), params.timestep(ii), params.maxIter(ii), tc.obstacles, tc.makePlots, tc.makeVideo);
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tc.testClass = tc.testClass.initialize(tc.domain, agents, params.barrierGain(ii), params.barrierExponent(ii), params.minAlt(ii), params.timestep(ii), params.maxIter(ii), obstacles, tc.makePlots, tc.makeVideo);
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% Save simulation parameters to output file
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tc.testClass.writeParams();
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@@ -148,7 +202,19 @@ classdef parametricTestSuite < matlab.unittest.TestCase
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% Cleanup
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tc.testClass = tc.testClass.teardown();
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end
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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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return;
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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
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