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fixed issues in sigmoid sensor model causing inverted response (annular partitions)

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This commit is contained in:
Kevin D
2025-11-24 17:39:16 -08:00
parent 66bbfe52ca
commit f7b28cdf4f
55 changed files with 44 additions and 31 deletions
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29
test/test_miSim.m
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@@ -42,8 +42,8 @@ classdef test_miSim < matlab.unittest.TestCase
betaTiltMax = 15;
alphaDistMin = 2.5;
alphaDistMax = 3;
alphaTiltMin = deg2rad(15);
alphaTiltMax = deg2rad(30);
alphaTiltMin = 15; % degrees
alphaTiltMax = 30; % degrees
% Communications
comRange = 8; % Maximum range between agents that forms a communications link
@@ -349,36 +349,38 @@ classdef test_miSim < matlab.unittest.TestCase
tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], tc.domain.center(1:2)), tc.domain, tc.discretizationStep, tc.protectedRange);
% Initialize agent collision geometry
dh = [0,0,-1]; % bias agent altitude from domain center
geometry1 = rectangularPrism;
geometry2 = geometry1;
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));
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));
geometry1 = geometry1.initialize([tc.domain.center + dh + [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh + [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 1));
geometry2 = geometry2.initialize([tc.domain.center + dh - [d, 0, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [d, 0, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 2));
% Initialize agent sensor model
sensor = sigmoidSensor;
% Homogeneous sensor model parameters
sensor = sensor.initialize(2.5, 3, NaN, NaN, deg2rad(15), 3);
sensor = sensor.initialize(2.75, 9, NaN, NaN, 22.5, 9);
f = sensor.plotParameters();
% Heterogeneous sensor model parameters
% 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));
% Initialize agents
tc.agents = {agent; agent};
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));
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));
tc.agents{1} = tc.agents{1}.initialize(tc.domain.center + dh + [d, 0, 0], zeros(1,3), 0, 0, geometry1, sensor, @gradientAscent, 3*d, 1, sprintf("Agent %d", 1));
tc.agents{2} = tc.agents{2}.initialize(tc.domain.center + dh - [d, 0, 0], zeros(1,3), 0, 0, geometry2, sensor, @gradientAscent, 3*d, 2, sprintf("Agent %d", 2));
% Optional third agent along the +Y axis
geometry3 = rectangularPrism;
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));
geometry3 = geometry3.initialize([tc.domain.center + dh - [0, d, 0] - tc.collisionRanges(1) * ones(1, 3); tc.domain.center + dh - [0, d, 0] + tc.collisionRanges(1) * ones(1, 3)], REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", 3));
tc.agents{3} = agent;
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));
tc.agents{3} = tc.agents{3}.initialize(tc.domain.center + dh - [0, d, 0], zeros(1, 3), 0, 0, geometry3, sensor, @gradientAscent, 3*d, 3, sprintf("Agent %d", 3));
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
end
function test_annular_partition(tc)
function test_single_partition(tc)
% make basic domain
tc.domain = tc.domain.initialize([zeros(1, 3); 10 * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
l = 10; % domain size
tc.domain = tc.domain.initialize([zeros(1, 3); l * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective
tc.domain.objective = tc.domain.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], tc.domain.center(1:2)), tc.domain, tc.discretizationStep, tc.protectedRange);
@@ -390,7 +392,9 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize agent sensor model
sensor = sigmoidSensor;
% Homogeneous sensor model parameters
sensor = sensor.initialize(2.5666, 5.0807, NaN, NaN, 0.3641, 13);
% sensor = sensor.initialize(2.5666, 5.0807, NaN, NaN, 20.8614, 13); % 13
alphaDist = l/2; % half of domain length/width
sensor = sensor.initialize(alphaDist, 3, NaN, NaN, 20, 3);
f = sensor.plotParameters();
% Initialize agents
@@ -399,6 +403,7 @@ classdef test_miSim < matlab.unittest.TestCase
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.domain.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
end
end

6
test/test_sigmoidSensor.m
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@@ -13,8 +13,8 @@ classdef test_sigmoidSensor < matlab.unittest.TestCase
betaTiltMax = 15;
alphaDistMin = 2.5;
alphaDistMax = 3;
alphaTiltMin = deg2rad(15);
alphaTiltMax = deg2rad(30);
alphaTiltMin = 15; % degrees
alphaTiltMax = 30; % degrees
end
methods (TestMethodSetup)
@@ -31,7 +31,7 @@ classdef test_sigmoidSensor < matlab.unittest.TestCase
tc.testClass = sigmoidSensor;
alphaDist = 2.5;
betaDist = 3;
alphaTilt = deg2rad(15);
alphaTilt = 15; % degrees
betaTilt = 3;
tc.testClass = tc.testClass.initialize(alphaDist, betaDist, NaN, NaN, alphaTilt, betaTilt);