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c5a7634d37
| Author | SHA1 | Date | |
|---|---|---|---|
| c5a7634d37 | |||
| bbefb6111b | |||
| ade795b3ae | |||
| db0ce2d42d |
3
.gitignore
vendored
3
.gitignore
vendored
@@ -38,3 +38,6 @@ codegen/
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# SimBiology backup files
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*.sbproj.backup
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*.sbproj.bak
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# Sandbox contents
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sandbox/*
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84
agent.m
84
agent.m
@@ -6,27 +6,34 @@ classdef agent
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% Sensor
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sensingFunction = @(r) 0.5; % probability of detection as a function of range
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sensingLength = 0.05; % length parameter used by sensing function
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% State
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pos = NaN(1, 3);
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vel = NaN(1, 3);
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cBfromC = NaN(3); % DCM body from sim cartesian (assume fixed for now)
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lastPos = NaN(1, 3); % position from previous timestep
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pos = NaN(1, 3); % current position
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vel = NaN(1, 3); % current velocity
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cBfromC = NaN(3); % current DCM body from sim cartesian (assume fixed for now)
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% Collision
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collisionGeometry;
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% Communication
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comRange = NaN;
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% Plotting
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scatterPoints;
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end
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methods (Access = public)
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function obj = initialize(obj, pos, vel, cBfromC, collisionGeometry, comRange, index, label)
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function obj = initialize(obj, pos, vel, cBfromC, collisionGeometry, sensingFunction, sensingLength, comRange, index, label)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'agent')};
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pos (1, 3) double;
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vel (1, 3) double;
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cBfromC (3, 3) double {mustBeDcm};
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collisionGeometry (1, 1) {mustBeGeometry};
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sensingFunction (1, 1) {mustBeA(sensingFunction, 'function_handle')} = @(r) 0.5;
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sensingLength (1, 1) double = NaN;
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comRange (1, 1) double = NaN;
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index (1, 1) double = NaN;
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label (1, 1) string = "";
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@@ -39,16 +46,72 @@ classdef agent
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obj.vel = vel;
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obj.cBfromC = cBfromC;
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obj.collisionGeometry = collisionGeometry;
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obj.sensingFunction = sensingFunction;
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obj.sensingLength = sensingLength;
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obj.comRange = comRange;
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obj.index = index;
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obj.label = label;
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end
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function f = plot(obj, f)
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function obj = run(obj, objectiveFunction, domain)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'agent')};
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objectiveFunction (1, 1) {mustBeA(objectiveFunction, 'function_handle')};
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domain (1, 1) {mustBeGeometry};
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, 'agent')};
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end
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% Do sensing to determine target position
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nextPos = obj.sensingFunction(objectiveFunction, domain, obj.pos, obj.sensingLength);
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% Move to next position
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% (dynamics not modeled at this time)
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obj.lastPos = obj.pos;
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obj.pos = nextPos;
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% Calculate movement
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d = obj.pos - obj.collisionGeometry.center;
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% Reinitialize collision geometry in the new position
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obj.collisionGeometry = obj.collisionGeometry.initialize([obj.collisionGeometry.minCorner; obj.collisionGeometry.maxCorner] + d, obj.collisionGeometry.tag, obj.collisionGeometry.label);
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end
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function updatePlots(obj)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'agent')};
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end
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arguments (Output)
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end
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% Scatterplot point positions
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for ii = 1:size(obj.scatterPoints, 1)
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obj.scatterPoints(ii).XData = obj.pos(1);
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obj.scatterPoints(ii).YData = obj.pos(2);
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obj.scatterPoints(ii).ZData = obj.pos(3);
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end
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% Find change in agent position since last timestep
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deltaPos = obj.pos - obj.lastPos;
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% Collision geometry edges
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for jj = 1:size(obj.collisionGeometry.lines, 2)
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% Update plotting
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for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
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obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
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obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
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obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
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end
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end
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% Network connections
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end
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function [obj, f] = plot(obj, f)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'agent')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, 'agent')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
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end
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@@ -63,10 +126,15 @@ classdef agent
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% Check if this is a tiled layout figure
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if strcmp(f.Children(1).Type, 'tiledlayout')
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% Add to other perspectives
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copyobj(o, f.Children(1).Children(2));
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copyobj(o, f.Children(1).Children(3));
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copyobj(o, f.Children(1).Children(5));
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o = [o; copyobj(o(1), f.Children(1).Children(2))];
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o = [o; copyobj(o(1), f.Children(1).Children(3))];
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o = [o; copyobj(o(1), f.Children(1).Children(5))];
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end
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obj.scatterPoints = o;
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% Plot collision geometry
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[obj.collisionGeometry, f] = obj.collisionGeometry.plotWireframe(f);
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end
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end
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end
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@@ -9,7 +9,7 @@ function f = firstPlotSetup(f)
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grid(f.Children(1).Children(1), "on");
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view(f.Children(1).Children(1), 0, 90);
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xlabel(f.Children(1).Children(1), "X"); ylabel(f.Children(1).Children(1), "Y");
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title("Top-down Perspective");
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title(f.Children(1).Children(1), "Top-down Perspective");
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% Communications graph
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nexttile(3, [1, 1]);
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@@ -17,33 +17,33 @@ function f = firstPlotSetup(f)
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axis(f.Children(1).Children(1), "image");
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grid(f.Children(1).Children(1), "off");
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view(f.Children(1).Children(1), 0, 0);
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title("Network Graph");
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title(f.Children(1).Children(1), "Network Graph");
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% 3D view
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title("3D Perspective");
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nexttile(4, [2, 2]);
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axes(f.Children(1).Children(1));
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axis(f.Children(1).Children(1), "image");
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grid(f.Children(1).Children(1), "on");
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view(f.Children(1).Children(1), 3);
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xlabel(f.Children(1).Children(1), "X"); ylabel(f.Children(1).Children(1), "Y"); zlabel(f.Children(1).Children(1), "Z");
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title(f.Children(1).Children(1), "3D Perspective");
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% Side-on view
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title("Side-on Perspective");
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nexttile(6, [2, 1]);
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axes(f.Children(1).Children(1));
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axis(f.Children(1).Children(1), "image");
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grid(f.Children(1).Children(1), "on");
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view(f.Children(1).Children(1), 90, 0);
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ylabel(f.Children(1).Children(1), "Y"); zlabel(f.Children(1).Children(1), "Z");
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title(f.Children(1).Children(1), "Side-on Perspective");
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% Front-on view
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title("Front-on Perspective");
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nexttile(10, [1, 2]);
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axes(f.Children(1).Children(1));
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axis(f.Children(1).Children(1), "image");
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grid(f.Children(1).Children(1), "on");
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view(f.Children(1).Children(1), 0, 0);
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xlabel(f.Children(1).Children(1), "X"); zlabel(f.Children(1).Children(1), "Z");
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title(f.Children(1).Children(1), "Front-on Perspective");
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end
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end
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@@ -1,23 +1,25 @@
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classdef rectangularPrism
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% Rectangular prism geometry
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properties (SetAccess = private, GetAccess = public)
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% Meta
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tag = REGION_TYPE.INVALID;
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label = "";
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% Spatial
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minCorner = NaN(1, 3);
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maxCorner = NaN(1, 3);
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dimensions = NaN(1, 3);
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center = NaN;
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footprint = NaN(4, 2);
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% Graph
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vertices = NaN(8, 3);
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edges = [1 2; 2 3; 3 4; 4 1; % bottom square
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5 6; 6 8; 8 7; 7 5; % top square
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1 5; 2 6; 3 8; 4 7]; % vertical edges
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footprint = NaN(4, 2);
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% Plotting
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lines;
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end
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methods (Access = public)
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@@ -161,12 +163,13 @@ classdef rectangularPrism
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c = (tmax >= 0) && (tmin <= 1);
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end
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function f = plotWireframe(obj, f)
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function [obj, f] = plotWireframe(obj, f)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
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end
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@@ -186,10 +189,12 @@ classdef rectangularPrism
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% Check if this is a tiled layout figure
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if strcmp(f.Children(1).Type, 'tiledlayout')
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% Add to other perspectives
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copyobj(o, f.Children(1).Children(2));
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copyobj(o, f.Children(1).Children(3));
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copyobj(o, f.Children(1).Children(5));
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o = [o, copyobj(o(:, 1), f.Children(1).Children(2))];
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o = [o, copyobj(o(:, 1), f.Children(1).Children(3))];
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o = [o, copyobj(o(:, 1), f.Children(1).Children(5))];
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end
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obj.lines = o;
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end
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end
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end
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162
miSim.m
162
miSim.m
@@ -3,6 +3,8 @@ classdef miSim
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% Simulation parameters
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properties (SetAccess = private, GetAccess = public)
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timestep = NaN; % delta time interval for simulation iterations
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maxIter = NaN; % maximum number of simulation iterations
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domain = rectangularPrism;
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objective = sensingObjective;
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obstacles = cell(0, 1); % geometries that define obstacles within the domain
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@@ -10,34 +12,149 @@ classdef miSim
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adjacency = NaN; % Adjacency matrix representing communications network graph
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end
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properties (Access = private)
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v = VideoWriter(fullfile('sandbox', strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'), '_miSimHist.mp4')));
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connectionsPlot; % objects for lines connecting agents in spatial plots
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graphPlot; % objects for abstract network graph plot
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end
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methods (Access = public)
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function obj = initialize(obj, domain, objective, agents, obstacles)
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function [obj, f] = initialize(obj, domain, objective, agents, timestep, maxIter, obstacles)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'miSim')};
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domain (1, 1) {mustBeGeometry};
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objective (1, 1) {mustBeA(objective, 'sensingObjective')};
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agents (:, 1) cell {mustBeAgents};
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timestep (:, 1) double = 0.05;
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maxIter (:, 1) double = 1000;
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obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, 'miSim')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
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end
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%% Define domain
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% Define simulation time parameters
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obj.timestep = timestep;
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obj.maxIter = maxIter;
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% Define domain
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obj.domain = domain;
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%% Add geometries representing obstacles within the domain
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% Add geometries representing obstacles within the domain
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obj.obstacles = obstacles;
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%% Define objective
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% Define objective
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obj.objective = objective;
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%% Define agents
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% Define agents
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obj.agents = agents;
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%% Compute adjacency matrix
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% Compute adjacency matrix
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obj = obj.updateAdjacency();
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% Set up initial plot
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% Set up axes arrangement
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% Plot domain
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[obj.domain, f] = obj.domain.plotWireframe();
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% Set plotting limits to focus on the domain
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xlim([obj.domain.minCorner(1), obj.domain.maxCorner(1)]);
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ylim([obj.domain.minCorner(2), obj.domain.maxCorner(2)]);
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zlim([obj.domain.minCorner(3), obj.domain.maxCorner(3)]);
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% Plot obstacles
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for ii = 1:size(obj.obstacles, 1)
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[obj.obstacles{ii}, f] = obj.obstacles{ii}.plotWireframe(f);
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end
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% Plot objective gradient
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f = obj.objective.plot(f);
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% Plot agents and their collision geometries
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for ii = 1:size(obj.agents, 1)
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[obj.agents{ii}, f] = obj.agents{ii}.plot(f);
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end
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% Plot communication links
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[obj, f] = obj.plotConnections(f);
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% Plot abstract network graph
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[obj, f] = obj.plotGraph(f);
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end
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function [obj, f] = run(obj, f)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, 'miSim')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
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end
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arguments (Output)
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obj (1, 1) {mustBeA(obj, 'miSim')};
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f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
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end
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% Create axes if they don't already exist
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f = firstPlotSetup(f);
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% Set up times to iterate over
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times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
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% Start video writer
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obj.v.FrameRate = 1/obj.timestep;
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obj.v.Quality = 90;
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obj.v.open();
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for ii = 1:size(times, 1)
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% Display current sim time
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t = times(ii);
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fprintf("Sim Time: %4.2f (%d/%d)\n", t, ii, obj.maxIter)
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% Iterate over agents to simulate their motion
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for jj = 1:size(obj.agents, 1)
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obj.agents{jj} = obj.agents{jj}.run(obj.objective.objectiveFunction, obj.domain);
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end
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% Update adjacency matrix
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obj = obj.updateAdjacency;
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% Update plots
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[obj, f] = obj.updatePlots(f);
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% Write frame in to video
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I = getframe(f);
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obj.v.writeVideo(I);
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end
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% Close video file
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obj.v.close();
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end
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function [obj, f] = updatePlots(obj, f)
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arguments (Input)
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||||
obj (1, 1) {mustBeA(obj, 'miSim')};
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||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
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||||
end
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||||
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% Update agent positions, collision geometries
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for ii = 1:size(obj.agents, 1)
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obj.agents{ii}.updatePlots();
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end
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% The remaining updates might be possible to do in a clever way
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% that moves existing lines instead of clearing and
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% re-plotting, which is much better for performance boost
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||||
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||||
% Update agent connections plot
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delete(obj.connectionsPlot);
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[obj, f] = obj.plotConnections(f);
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% Update network graph plot
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delete(obj.graphPlot);
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[obj, f] = obj.plotGraph(f);
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||||
drawnow;
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||||
end
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||||
function obj = updateAdjacency(obj)
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arguments (Input)
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||||
@@ -54,19 +171,26 @@ classdef miSim
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for ii = 2:size(A, 1)
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for jj = 1:(ii - 1)
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if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) <= min([obj.agents{ii}.comRange, obj.agents{jj}.comRange])
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A(ii, jj) = true;
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% Make sure that obstacles don't obstruct the line
|
||||
% of sight, breaking the connection
|
||||
for kk = 1:size(obj.obstacles, 1)
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if ~obj.obstacles{kk}.containsLine(obj.agents{ii}.pos, obj.agents{jj}.pos)
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A(ii, jj) = 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
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||||
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||||
obj.adjacency = A | A';
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||||
end
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||||
function f = plotNetwork(obj, f)
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||||
function [obj, f] = plotConnections(obj, f)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
|
||||
end
|
||||
|
||||
@@ -86,36 +210,34 @@ classdef miSim
|
||||
|
||||
% Plot the connections
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||||
hold(f.CurrentAxes, "on");
|
||||
o = plot3(X, Y, Z, 'Color', 'g', 'LineWidth', 1, 'LineStyle', '--');
|
||||
o = plot3(X, Y, Z, 'Color', 'g', 'LineWidth', 2, 'LineStyle', '--');
|
||||
hold(f.CurrentAxes, "off");
|
||||
|
||||
% Check if this is a tiled layout figure
|
||||
if strcmp(f.Children(1).Type, 'tiledlayout')
|
||||
% Add to other plots
|
||||
copyobj(o, f.Children(1).Children(2));
|
||||
copyobj(o, f.Children(1).Children(3));
|
||||
copyobj(o, f.Children(1).Children(5));
|
||||
o = [o, copyobj(o(:, 1), f.Children(1).Children(2))];
|
||||
o = [o, copyobj(o(:, 1), f.Children(1).Children(3))];
|
||||
o = [o, copyobj(o(:, 1), f.Children(1).Children(5))];
|
||||
end
|
||||
|
||||
obj.connectionsPlot = o;
|
||||
end
|
||||
function f = plotGraph(obj, f)
|
||||
function [obj, f] = plotGraph(obj, f)
|
||||
arguments (Input)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
|
||||
end
|
||||
arguments (Output)
|
||||
obj (1, 1) {mustBeA(obj, 'miSim')};
|
||||
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
|
||||
end
|
||||
|
||||
% Form graph from adjacency matrix
|
||||
G = graph(obj.adjacency, 'omitselfloops');
|
||||
|
||||
% Check if this is a tiled layout figure
|
||||
if strcmp(f.Children(1).Type, 'tiledlayout')
|
||||
o = plot(f.Children(1).Children(4), G, 'LineStyle', '--', 'EdgeColor', 'g', 'NodeColor', 'k');
|
||||
else
|
||||
o = plot(f.CurrentAxes, G, 'LineStyle', '--', 'EdgeColor', 'g', 'NodeColor', 'k');
|
||||
end
|
||||
|
||||
% Plot graph object
|
||||
obj.graphPlot = plot(f.Children(1).Children(4), G, 'LineStyle', '--', 'EdgeColor', 'g', 'NodeColor', 'k', 'LineWidth', 2);
|
||||
end
|
||||
end
|
||||
|
||||
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info Ref="sensingFunctions" Type="Relative"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="9c9ce3cb-5989-41e8-a20d-358a95c08b20" type="Reference"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info Ref="sandbox" Type="Relative"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="ff13e617-a2ad-49b1-a9b5-668ac2cffc4a" type="Reference"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="1" type="DIR_SIGNIFIER"/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info/>
|
||||
@@ -0,0 +1,2 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<Info location="sandbox" type="File"/>
|
||||
44
sensingFunctions/basicGradientAscent.m
Normal file
44
sensingFunctions/basicGradientAscent.m
Normal file
@@ -0,0 +1,44 @@
|
||||
function nextPos = basicGradientAscent(objectiveFunction, domain, pos, r)
|
||||
arguments (Input)
|
||||
objectiveFunction (1, 1) {mustBeA(objectiveFunction, 'function_handle')};
|
||||
domain (1, 1) {mustBeGeometry};
|
||||
pos (1, 3) double;
|
||||
r (1, 1) double;
|
||||
end
|
||||
arguments (Output)
|
||||
nextPos(1, 3) double;
|
||||
end
|
||||
|
||||
% Evaluate objective at position offsets +/-[r, 0, 0] and +/-[0, r, 0]
|
||||
currentPos = pos(1:2);
|
||||
neighborPos = [currentPos(1) + r, currentPos(2); ... % (+x)
|
||||
currentPos(1), currentPos(2) + r; ... % (+y)
|
||||
currentPos(1) - r, currentPos(2); ... % (-x)
|
||||
currentPos(1), currentPos(2) - r; ... % (-y)
|
||||
];
|
||||
|
||||
% Check for neighbor positions that fall outside of the domain
|
||||
outOfBounds = false(size(neighborPos, 1), 1);
|
||||
for ii = 1:size(neighborPos, 1)
|
||||
if ~domain.contains([neighborPos(ii, :), 0])
|
||||
outOfBounds(ii) = true;
|
||||
end
|
||||
end
|
||||
|
||||
% Replace out of bounds positions with inoffensive in-bounds positions
|
||||
neighborPos(outOfBounds, 1:3) = repmat(pos, sum(outOfBounds), 1);
|
||||
|
||||
% Sense values at selected positions
|
||||
neighborValues = [objectiveFunction(neighborPos(1, 1), neighborPos(1, 2)), ... % (+x)
|
||||
objectiveFunction(neighborPos(2, 1), neighborPos(2, 2)), ... % (+y)
|
||||
objectiveFunction(neighborPos(3, 1), neighborPos(3, 2)), ... % (-x)
|
||||
objectiveFunction(neighborPos(4, 1), neighborPos(4, 2)), ... % (-y)
|
||||
];
|
||||
|
||||
% Prevent out of bounds locations from ever possibly being selected
|
||||
neighborValues(outOfBounds) = 0;
|
||||
|
||||
% Select next position by maximum sensed value
|
||||
nextPos = neighborPos(neighborValues == max(neighborValues), :);
|
||||
nextPos = [nextPos(1, 1:2), pos(3)]; % just in case two get selected, simply pick one
|
||||
end
|
||||
183
test_miSim.m
183
test_miSim.m
@@ -4,6 +4,8 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
|
||||
% Domain
|
||||
domain = rectangularPrism; % domain geometry
|
||||
maxIter = 1000;
|
||||
timestep = 0.05
|
||||
|
||||
% Obstacles
|
||||
minNumObstacles = 1; % Minimum number of obstacles to be randomly generated
|
||||
@@ -20,6 +22,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
% Agents
|
||||
minAgents = 3; % Minimum number of agents to be randomly generated
|
||||
maxAgents = 9; % Maximum number of agents to be randomly generated
|
||||
sensingLength = 0.05; % length parameter used by sensing function
|
||||
agents = cell(0, 1);
|
||||
|
||||
% Collision
|
||||
@@ -74,7 +77,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
methods (Test)
|
||||
% Test methods
|
||||
function misim_initialization(tc)
|
||||
% randomly create 2-3 obstacles
|
||||
% randomly create obstacles
|
||||
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
|
||||
tc.obstacles = cell(nGeom, 1);
|
||||
|
||||
@@ -184,7 +187,7 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
|
||||
% Initialize candidate agent
|
||||
candidateGeometry = rectangularPrism;
|
||||
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), eye(3),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)), tc.comRange, ii, sprintf("Agent %d", ii));
|
||||
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), eye(3),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)), @(r) 0.5, tc.sensingLength, tc.comRange, ii, sprintf("Agent %d", ii));
|
||||
|
||||
% Make sure candidate agent doesn't collide with
|
||||
% domain
|
||||
@@ -232,35 +235,171 @@ classdef test_miSim < matlab.unittest.TestCase
|
||||
end
|
||||
|
||||
% Initialize the simulation
|
||||
tc.testClass = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.obstacles);
|
||||
[tc.testClass, f] = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.timestep, tc.maxIter, tc.obstacles);
|
||||
end
|
||||
function misim_run(tc)
|
||||
% randomly create obstacles
|
||||
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
|
||||
tc.obstacles = cell(nGeom, 1);
|
||||
|
||||
% Plot domain
|
||||
f = tc.testClass.domain.plotWireframe;
|
||||
% Iterate over obstacles to initialize
|
||||
for ii = 1:size(tc.obstacles, 1)
|
||||
badCandidate = true;
|
||||
while badCandidate
|
||||
% Instantiate a rectangular prism obstacle
|
||||
tc.obstacles{ii} = rectangularPrism;
|
||||
|
||||
% Set plotting limits to focus on the domain
|
||||
xlim([tc.testClass.domain.minCorner(1), tc.testClass.domain.maxCorner(1)]);
|
||||
ylim([tc.testClass.domain.minCorner(2), tc.testClass.domain.maxCorner(2)]);
|
||||
zlim([tc.testClass.domain.minCorner(3), tc.testClass.domain.maxCorner(3)]);
|
||||
% Randomly generate min corner for the obstacle
|
||||
candidateMinCorner = tc.domain.random();
|
||||
candidateMinCorner = [candidateMinCorner(1:2), 0]; % bind obstacles to floor of domain
|
||||
|
||||
% Plot obstacles
|
||||
for ii = 1:size(tc.testClass.obstacles, 1)
|
||||
tc.testClass.obstacles{ii}.plotWireframe(f);
|
||||
% Randomly select a corresponding maximum corner that
|
||||
% satisfies min/max obstacle size specifications
|
||||
candidateMaxCorner = candidateMinCorner + tc.minObstacleSize + rand(1, 3) * (tc.maxObstacleSize - tc.minObstacleSize);
|
||||
|
||||
% Initialize obstacle
|
||||
tc.obstacles{ii} = tc.obstacles{ii}.initialize([candidateMinCorner; candidateMaxCorner], REGION_TYPE.OBSTACLE, sprintf("Column obstacle %d", ii));
|
||||
|
||||
% Check if the obstacle intersects with any existing
|
||||
% obstacles
|
||||
violation = false;
|
||||
for kk = 1:(ii - 1)
|
||||
if geometryIntersects(tc.obstacles{kk}, tc.obstacles{ii})
|
||||
violation = true;
|
||||
break;
|
||||
end
|
||||
end
|
||||
if violation
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure that the obstacles are fully contained by
|
||||
% the domain
|
||||
if ~domainContainsObstacle(tc.domain, tc.obstacles{ii})
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure that the obstacles don't cover the sensing
|
||||
% objective
|
||||
if obstacleCoversObjective(tc.objective, tc.obstacles{ii})
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure that the obstacles aren't too close to the
|
||||
% sensing objective
|
||||
if obstacleCrowdsObjective(tc.objective, tc.obstacles{ii}, tc.protectedRange)
|
||||
continue;
|
||||
end
|
||||
|
||||
badCandidate = false;
|
||||
end
|
||||
end
|
||||
|
||||
% Plot objective gradient
|
||||
f = tc.testClass.objective.plot(f);
|
||||
% Add agents individually, ensuring that each addition does not
|
||||
% invalidate the initialization setup
|
||||
for ii = 1:size(tc.agents, 1)
|
||||
initInvalid = true;
|
||||
while initInvalid
|
||||
candidatePos = [tc.objective.groundPos, 0];
|
||||
% Generate a random position for the agent based on
|
||||
% existing agent positions
|
||||
if ii == 1
|
||||
while agentsCrowdObjective(tc.objective, candidatePos, mean(tc.domain.dimensions) / 2)
|
||||
candidatePos = tc.domain.random();
|
||||
end
|
||||
else
|
||||
candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.comRange/sqrt(2));
|
||||
end
|
||||
|
||||
% Plot agents and their collision geometries
|
||||
for ii = 1:size(tc.testClass.agents, 1)
|
||||
f = tc.testClass.agents{ii}.plot(f);
|
||||
f = tc.testClass.agents{ii}.collisionGeometry.plotWireframe(f);
|
||||
% Make sure that the candidate position is within the
|
||||
% domain
|
||||
if ~tc.domain.contains(candidatePos)
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure that the candidate position does not crowd
|
||||
% the sensing objective and create boring scenarios
|
||||
if agentsCrowdObjective(tc.objective, candidatePos, mean(tc.domain.dimensions) / 2)
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure that there exist unobstructed lines of sight at
|
||||
% appropriate ranges to form a connected communications
|
||||
% graph between the agents
|
||||
connections = false(1, ii - 1);
|
||||
for jj = 1:(ii - 1)
|
||||
if norm(tc.agents{jj}.pos - candidatePos) <= tc.comRange
|
||||
% Check new agent position against all existing
|
||||
% agent positions for communications range
|
||||
connections(jj) = true;
|
||||
for kk = 1:size(tc.obstacles, 1)
|
||||
if tc.obstacles{kk}.containsLine(tc.agents{jj}.pos, candidatePos)
|
||||
connections(jj) = false;
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
||||
|
||||
% New agent must be connected to an existing agent to
|
||||
% be valid
|
||||
if ii ~= 1 && ~any(connections)
|
||||
continue;
|
||||
end
|
||||
|
||||
% Initialize candidate agent
|
||||
candidateGeometry = rectangularPrism;
|
||||
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), eye(3),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)), @basicGradientAscent, tc.sensingLength, tc.comRange, ii, sprintf("Agent %d", ii));
|
||||
|
||||
% Make sure candidate agent doesn't collide with
|
||||
% domain
|
||||
violation = false;
|
||||
for jj = 1:size(newAgent.collisionGeometry.vertices, 1)
|
||||
% Check if collision geometry exits domain
|
||||
if ~tc.domain.contains(newAgent.collisionGeometry.vertices(jj, 1:3))
|
||||
violation = true;
|
||||
break;
|
||||
end
|
||||
end
|
||||
if violation
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure candidate doesn't collide with obstacles
|
||||
violation = false;
|
||||
for kk = 1:size(tc.obstacles, 1)
|
||||
if geometryIntersects(tc.obstacles{kk}, newAgent.collisionGeometry)
|
||||
violation = true;
|
||||
break;
|
||||
end
|
||||
end
|
||||
if violation
|
||||
continue;
|
||||
end
|
||||
|
||||
% Make sure candidate doesn't collide with existing
|
||||
% agents
|
||||
violation = false;
|
||||
for kk = 1:(ii - 1)
|
||||
if geometryIntersects(tc.agents{kk}.collisionGeometry, newAgent.collisionGeometry)
|
||||
violation = true;
|
||||
break;
|
||||
end
|
||||
end
|
||||
if violation
|
||||
continue;
|
||||
end
|
||||
|
||||
% Candidate agent is valid, store to pass in to sim
|
||||
initInvalid = false;
|
||||
tc.agents{ii} = newAgent;
|
||||
end
|
||||
end
|
||||
|
||||
% Plot communication links
|
||||
f = tc.testClass.plotNetwork(f);
|
||||
% Initialize the simulation
|
||||
[tc.testClass, f] = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.timestep, tc.maxIter, tc.obstacles);
|
||||
|
||||
% Plot abstract network graph
|
||||
f = tc.testClass.plotGraph(f);
|
||||
% Run simulation loop
|
||||
[tc.testClass, f] = tc.testClass.run(f);
|
||||
end
|
||||
end
|
||||
end
|
||||
Reference in New Issue
Block a user