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scenario csv on both platforms

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This commit is contained in:
Kevin Dee
2026-02-28 19:36:58 -08:00
parent 0bf293c95e
commit 387d6aea56
15 changed files with 739 additions and 293 deletions
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112
@miSim/initializeFromCsv.m
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@@ -1,12 +1,106 @@
function obj = initializeFromCsv(obj, csvPath)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
csvPath (1, 1) string;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
% INITIALIZEFROMCSV Initialize miSim from an AERPAW scenario CSV file.
%
% Reads all guidance parameters, domain geometry, initial UAV positions,
% and obstacle definitions from the CSV, then builds and initialises the
% simulation. Ends by calling the standard obj.initialize(...) method.
%
% This is the MATLAB-path counterpart to the compiled path that unpacks a
% flat scenarioParams array in guidance_step.m. It is only ever called
% from within a coder.target('MATLAB') guard and is never compiled.
%
% Usage (inside guidance_step.m on MATLAB path):
% sim = sim.initializeFromCsv('aerpaw/config/scenario.csv');
%
% Expected CSV columns (see scenario.csv):
% timestep, maxIter, minAlt, discretizationStep, protectedRange,
% initialStepSize, barrierGain, barrierExponent, collisionRadius, comRange,
% alphaDist, betaDist, alphaTilt, betaTilt,
% domainMin ("x,y,z"), domainMax ("x,y,z"), objectivePos ("x,y"),
% initialPositions (flat "x1,y1,z1, x2,y2,z2,..."),
% numObstacles, obstacleMin (flat), obstacleMax (flat)
params = obj.readScenarioCsv(tc.csvPath);
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
csvPath (1, 1) string;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
end
% ---- Parse CSV via readScenarioCsv ---------------------------------------
scenario = obj.readScenarioCsv(csvPath);
TIMESTEP = scenario.timestep;
MAX_ITER = scenario.maxIter;
MIN_ALT = scenario.minAlt;
DISCRETIZATION_STEP = scenario.discretizationStep;
PROTECTED_RANGE = scenario.protectedRange;
INITIAL_STEP_SIZE = scenario.initialStepSize;
BARRIER_GAIN = scenario.barrierGain;
BARRIER_EXPONENT = scenario.barrierExponent;
COLLISION_RADIUS = scenario.collisionRadius;
COMMS_RANGE = scenario.comRange;
ALPHA_DIST = scenario.alphaDist;
BETA_DIST = scenario.betaDist;
ALPHA_TILT = scenario.alphaTilt;
BETA_TILT = scenario.betaTilt;
DOMAIN_MIN = scenario.domainMin; % 1×3
DOMAIN_MAX = scenario.domainMax; % 1×3
OBJECTIVE_GROUND_POS = scenario.objectivePos; % 1×2
SENSOR_PERFORMANCE_MINIMUM = scenario.sensorPerformanceMinimum; % scalar
% Initial UAV positions: flat vector reshaped to N×3
flatPos = scenario.initialPositions; % 1×(3*N)
assert(mod(numel(flatPos), 3) == 0, ...
"initialPositions must have a multiple of 3 values; got %d", numel(flatPos));
positions = reshape(flatPos, 3, [])'; % N×3
numAgents = size(positions, 1);
numObstacles = scenario.numObstacles;
% ---- Build domain --------------------------------------------------------
dom = rectangularPrism;
dom = dom.initialize([DOMAIN_MIN; DOMAIN_MAX], REGION_TYPE.DOMAIN, "Guidance Domain");
% ---- Build sensing objective (MATLAB path: objectiveFunctionWrapper) -----
dom.objective = sensingObjective;
objFcn = objectiveFunctionWrapper(OBJECTIVE_GROUND_POS, 3 * eye(2));
dom.objective = dom.objective.initialize(objFcn, dom, DISCRETIZATION_STEP, PROTECTED_RANGE, SENSOR_PERFORMANCE_MINIMUM);
% ---- Build shared sensor model -------------------------------------------
sensor = sigmoidSensor;
sensor = sensor.initialize(ALPHA_DIST, BETA_DIST, ALPHA_TILT, BETA_TILT);
% ---- Initialise agents from scenario positions ---------------------------
agentList = cell(numAgents, 1);
for ii = 1:numAgents
pos = positions(ii, :);
geom = spherical;
geom = geom.initialize(pos, COLLISION_RADIUS, REGION_TYPE.COLLISION, ...
sprintf("UAV %d Collision", ii));
ag = agent;
ag = ag.initialize(pos, geom, sensor, COMMS_RANGE, MAX_ITER, ...
INITIAL_STEP_SIZE, sprintf("UAV %d", ii));
agentList{ii} = ag;
end
% ---- Build obstacles from CSV --------------------------------------------
obstacleList = cell(numObstacles, 1);
if numObstacles > 0
obsMin = reshape(scenario.obstacleMin, 3, numObstacles)'; % N×3
obsMax = reshape(scenario.obstacleMax, 3, numObstacles)';
for ii = 1:numObstacles
obs = rectangularPrism;
obs = obs.initialize([obsMin(ii, :); obsMax(ii, :)], ...
REGION_TYPE.OBSTACLE, sprintf("Obstacle %d", ii));
obstacleList{ii} = obs;
end
end
% ---- Initialise simulation (plots and video disabled) --------------------
obj = obj.initialize(dom, agentList, BARRIER_GAIN, BARRIER_EXPONENT, ...
MIN_ALT, TIMESTEP, MAX_ITER, obstacleList, false, false);
end