36 Commits

Author SHA1 Message Date
a2eb95381d added cone geometry, implemented fov visualization 2025-11-13 09:39:02 -08:00
3d35179579 partitioning introduced to main loop 2025-11-12 18:13:43 -08:00
9e948072e8 implemented partitioning 2025-11-11 12:50:43 -08:00
74088a13f3 potential videowriter compat fix 2025-11-10 13:29:44 -08:00
8b14bfc5ce refactored agent sensing and guidance 2025-11-09 22:17:21 -08:00
c7510812cb updated plotting 2025-11-09 16:41:09 -08:00
b63bbadfb4 starting sensor model 2025-10-28 13:16:29 -07:00
f50beeab5b starting sensor model 2025-10-28 13:04:33 -07:00
d36d2cab3e Merge branch 'main' into dev 2025-10-27 23:25:53 -07:00
2b58646aca fixed filename 2025-10-27 23:23:11 -07:00
0621e0a07a added video writing feature 2025-10-27 23:23:11 -07:00
7fb9d13781 geometries move in plots as sim runs 2025-10-27 23:23:11 -07:00
faa8bad596 implemented basic gradient ascent 2025-10-27 23:23:11 -07:00
8955d4d29b fixed bug allowing obstructed coms connections 2025-10-27 23:23:11 -07:00
f953cd3882 added abstract network graph plot 2025-10-27 23:23:11 -07:00
b2787e1e53 Added connections to plots 2025-10-27 23:23:11 -07:00
8af5e87272 added multiple visualization perspectives 2025-10-27 23:23:11 -07:00
d0a060f404 fixed collision detection in initialization 2025-10-27 23:23:11 -07:00
2f0647caf3 fixed init generation being really slow 2025-10-27 23:23:11 -07:00
5a9ac0c2d5 protected objective from domain edges 2025-10-27 23:23:11 -07:00
c61d627f0d stopped randomly placing agents too close to objective, fixed row/col preference 2025-10-27 23:23:11 -07:00
da3f732250 refined domain and obstacle generation 2025-10-27 23:23:11 -07:00
7fff074a5c created project file 2025-10-27 23:23:11 -07:00
66a5dfe1e6 fixed filename 2025-10-27 23:16:25 -07:00
c5a7634d37 added video writing feature 2025-10-27 23:13:33 -07:00
bbefb6111b geometries move in plots as sim runs 2025-10-27 22:38:39 -07:00
ade795b3ae implemented basic gradient ascent 2025-10-27 21:29:54 -07:00
db0ce2d42d fixed bug allowing obstructed coms connections 2025-10-27 20:45:37 -07:00
5c6eeed6fd added abstract network graph plot 2025-10-27 19:52:10 -07:00
f8a36eec4b Added connections to plots 2025-10-27 19:42:59 -07:00
22fab26485 added multiple visualization perspectives 2025-10-27 09:22:20 -07:00
c64fc3eae5 fixed collision detection in initialization 2025-10-26 19:45:32 -07:00
fdbd90afdf fixed init generation being really slow 2025-10-26 19:14:50 -07:00
b82c87520a protected objective from domain edges 2025-10-26 13:30:09 -07:00
78538ab586 stopped randomly placing agents too close to objective, fixed row/col preference 2025-10-25 23:41:12 -07:00
c5a2b644d8 refined domain and obstacle generation 2025-10-25 18:22:06 -07:00
78 changed files with 1652 additions and 320 deletions

3
.gitignore vendored
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@@ -38,3 +38,6 @@ codegen/
# SimBiology backup files
*.sbproj.backup
*.sbproj.bak
# Sandbox contents
sandbox/*

132
agent.m
View File

@@ -5,25 +5,44 @@ classdef agent
label = "";
% Sensor
sensingFunction = @(r) 0.5; % probability of detection as a function of range
sensorModel;
sensingLength = 0.05; % length parameter used by sensing function
% Guidance
guidanceModel;
% State
pos = NaN(1, 3);
vel = NaN(1, 3);
cBfromC = NaN(3); % DCM body from sim cartesian (assume fixed for now)
lastPos = NaN(1, 3); % position from previous timestep
pos = NaN(1, 3); % current position
vel = NaN(1, 3); % current velocity
pan = NaN; % pan angle
tilt = NaN; % tilt angle
% Collision
collisionGeometry;
% FOV cone
fovGeometry;
% Communication
comRange = NaN;
% Plotting
scatterPoints;
end
methods (Access = public)
function obj = initialize(obj, pos, vel, cBfromC, collisionGeometry, index, label)
function obj = initialize(obj, pos, vel, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
pos (1, 3) double;
vel (1, 3) double;
cBfromC (3, 3) double {mustBeDcm};
collisionGeometry (1, 1) {mustBeConstraintGeometries};
pan (1, 1) double;
tilt (1, 1) double;
collisionGeometry (1, 1) {mustBeGeometry};
sensorModel (1, 1) {mustBeSensor}
guidanceModel (1, 1) {mustBeA(guidanceModel, 'function_handle')};
comRange (1, 1) double = NaN;
index (1, 1) double = NaN;
label (1, 1) string = "";
end
@@ -33,17 +52,90 @@ classdef agent
obj.pos = pos;
obj.vel = vel;
obj.cBfromC = cBfromC;
obj.pan = pan;
obj.tilt = tilt;
obj.collisionGeometry = collisionGeometry;
obj.sensorModel = sensorModel;
obj.guidanceModel = guidanceModel;
obj.comRange = comRange;
obj.index = index;
obj.label = label;
% Initialize FOV cone
obj.fovGeometry = cone;
obj.fovGeometry = obj.fovGeometry.initialize([obj.pos(1:2), 0], obj.sensorModel.r, obj.pos(3), REGION_TYPE.FOV, sprintf("%s FOV", obj.label));
end
function f = plot(obj, f)
function obj = run(obj, sensingObjective, domain, partitioning)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
domain (1, 1) {mustBeGeometry};
partitioning (:, :) double;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'agent')};
end
% Do sensing
[sensedValues, sensedPositions] = obj.sensorModel.sense(obj, sensingObjective, domain, partitioning);
% Determine next planned position
nextPos = obj.guidanceModel(sensedValues, sensedPositions, obj.pos);
% Move to next position
% (dynamics not modeled at this time)
obj.lastPos = obj.pos;
obj.pos = nextPos;
% Calculate movement
d = obj.pos - obj.collisionGeometry.center;
% Reinitialize collision geometry in the new position
obj.collisionGeometry = obj.collisionGeometry.initialize([obj.collisionGeometry.minCorner; obj.collisionGeometry.maxCorner] + d, obj.collisionGeometry.tag, obj.collisionGeometry.label);
end
function updatePlots(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
end
arguments (Output)
end
% Scatterplot point positions
for ii = 1:size(obj.scatterPoints, 1)
obj.scatterPoints(ii).XData = obj.pos(1);
obj.scatterPoints(ii).YData = obj.pos(2);
obj.scatterPoints(ii).ZData = obj.pos(3);
end
% Find change in agent position since last timestep
deltaPos = obj.pos - obj.lastPos;
% Collision geometry edges
for jj = 1:size(obj.collisionGeometry.lines, 2)
% Update plotting
for ii = 1:size(obj.collisionGeometry.lines(:, jj), 1)
obj.collisionGeometry.lines(ii, jj).XData = obj.collisionGeometry.lines(ii, jj).XData + deltaPos(1);
obj.collisionGeometry.lines(ii, jj).YData = obj.collisionGeometry.lines(ii, jj).YData + deltaPos(2);
obj.collisionGeometry.lines(ii, jj).ZData = obj.collisionGeometry.lines(ii, jj).ZData + deltaPos(3);
end
end
% Update FOV geometry surfaces
for jj = 1:size(obj.fovGeometry.surface, 2)
% Update each plot
obj.fovGeometry.surface(jj).XData = obj.fovGeometry.surface(jj).XData + deltaPos(1);
obj.fovGeometry.surface(jj).YData = obj.fovGeometry.surface(jj).YData + deltaPos(2);
obj.fovGeometry.surface(jj).ZData = obj.fovGeometry.surface(jj).ZData + deltaPos(3);
end
end
function [obj, f] = plot(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'agent')};
ind (1, :) double = NaN;
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'agent')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
@@ -51,9 +143,25 @@ classdef agent
f = firstPlotSetup(f);
% Plot points representing the agent position
hold(f.CurrentAxes, "on");
scatter3(obj.pos(1), obj.pos(2), obj.pos(3), 'filled', 'ko', 'SizeData', 50);
hold(f.CurrentAxes, "off");
hold(f.Children(1).Children(end), "on");
o = scatter3(f.Children(1).Children(end), obj.pos(1), obj.pos(2), obj.pos(3), 'filled', 'ko', 'SizeData', 25);
hold(f.Children(1).Children(end), "off");
% Check if this is a tiled layout figure
if strcmp(f.Children(1).Type, 'tiledlayout')
% Add to other perspectives
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(4))];
end
obj.scatterPoints = o;
% Plot collision geometry
[obj.collisionGeometry, f] = obj.collisionGeometry.plotWireframe(ind, f);
% Plot FOV geometry
[obj.fovGeometry, f] = obj.fovGeometry.plot(ind, f);
end
end
end

View File

@@ -1,8 +1,78 @@
function f = firstPlotSetup(f)
arguments (Input)
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
if isempty(f.CurrentAxes)
axes(f);
axis(f.CurrentAxes, "equal");
grid(f.CurrentAxes, "on");
view(f.CurrentAxes, 3);
tiledlayout(f, 5, 5, "TileSpacing", "tight", "Padding", "compact");
% 3D view
nexttile(1, [4, 5]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "on");
view(f.Children(1).Children(1), 3);
xlabel(f.Children(1).Children(1), "X"); ylabel(f.Children(1).Children(1), "Y"); zlabel(f.Children(1).Children(1), "Z");
title(f.Children(1).Children(1), "3D View");
% Communications graph
nexttile(21, [1, 1]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "off");
view(f.Children(1).Children(1), 0, 90);
title(f.Children(1).Children(1), "Network Graph");
set(f.Children(1).Children(1), 'XTickLabelMode', 'manual');
set(f.Children(1).Children(1), 'YTickLabelMode', 'manual');
set(f.Children(1).Children(1), 'XTickLabel', {});
set(f.Children(1).Children(1), 'YTickLabel', {});
set(f.Children(1).Children(1), 'XTick', []);
set(f.Children(1).Children(1), 'YTick', []);
set(f.Children(1).Children(1), 'XColor', 'none');
set(f.Children(1).Children(1), 'YColor', 'none');
% Top-down view
nexttile(22, [1, 1]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "on");
view(f.Children(1).Children(1), 0, 90);
xlabel(f.Children(1).Children(1), "X"); ylabel(f.Children(1).Children(1), "Y");
title(f.Children(1).Children(1), "Top-down View");
% Side-on view
nexttile(23, [1, 1]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "on");
view(f.Children(1).Children(1), 90, 0);
ylabel(f.Children(1).Children(1), "Y"); zlabel(f.Children(1).Children(1), "Z");
title(f.Children(1).Children(1), "Side-on View");
% Front-on view
nexttile(24, [1, 1]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "on");
view(f.Children(1).Children(1), 0, 0);
xlabel(f.Children(1).Children(1), "X"); zlabel(f.Children(1).Children(1), "Z");
title(f.Children(1).Children(1), "Front-on View");
% Partitioning
nexttile(25, [1, 1]);
axes(f.Children(1).Children(1));
axis(f.Children(1).Children(1), "image");
grid(f.Children(1).Children(1), "on");
view(f.Children(1).Children(1), 0, 90);
xlabel(f.Children(1).Children(1), "X"); ylabel(f.Children(1).Children(1), "Y");
title(f.Children(1).Children(1), "Domain Partitioning");
set(f.Children(1).Children(1), 'XTickLabelMode', 'manual');
set(f.Children(1).Children(1), 'YTickLabelMode', 'manual');
set(f.Children(1).Children(1), 'XTickLabel', {});
set(f.Children(1).Children(1), 'YTickLabel', {});
set(f.Children(1).Children(1), 'XTick', []);
set(f.Children(1).Children(1), 'YTick', []);
end
end

View File

@@ -8,6 +8,7 @@ classdef REGION_TYPE
DOMAIN (1, [0, 0, 0]); % domain region
OBSTACLE (2, [255, 127, 127]); % obstacle region
COLLISION (3, [255, 255, 128]); % collision avoidance region
FOV (4, [255, 165, 0]); % field of view region
end
methods
function obj = REGION_TYPE(id, color)

82
geometries/cone.m Normal file
View File

@@ -0,0 +1,82 @@
classdef cone
% Conical geometry
properties (SetAccess = private, GetAccess = public)
% Meta
tag = REGION_TYPE.INVALID;
label = "";
% Spatial
center = NaN;
radius = NaN;
height = NaN;
% Plotting
surface;
n = 32;
end
methods
function obj = initialize(obj, center, radius, height, tag, label)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'cone')};
center (1, 3) double;
radius (1, 1) double;
height (1, 1) double;
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
label (1, 1) string = "";
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'cone')};
end
obj.center = center;
obj.radius = radius;
obj.height = height;
obj.tag = tag;
obj.label = label;
end
function [obj, f] = plot(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'cone')};
ind (1, :) double = NaN;
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'cone')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
% Create axes if they don't already exist
f = firstPlotSetup(f);
% Plot cone
[X, Y, Z] = cylinder([obj.radius, 0], obj.n);
% Scale to match height
Z = Z * obj.height;
% Move to center location
X = X + obj.center(1);
Y = Y + obj.center(2);
Z = Z + obj.center(3);
% Plot
if isnan(ind)
o = surf(f.CurrentAxes, X, Y, Z);
else
hold(f.Children(1).Children(ind(1)), "on");
o = surf(f.Children(1).Children(ind(1)), X, Y, Z, ones([size(Z), 1]) .* reshape(obj.tag.color, 1, 1, 3), 'FaceAlpha', 0.25, 'EdgeColor', 'none');
hold(f.Children(1).Children(ind(1)), "off");
end
% Copy to other requested tiles
if numel(ind) > 1
for ii = 2:size(ind, 2)
o = [o, copyobj(o(:, 1), f.Children(1).Children(ind(ii)))];
end
end
obj.surface = o;
end
end
end

View File

@@ -0,0 +1,204 @@
classdef rectangularPrism
% Rectangular prism geometry
properties (SetAccess = private, GetAccess = public)
% Meta
tag = REGION_TYPE.INVALID;
label = "";
% Spatial
minCorner = NaN(1, 3);
maxCorner = NaN(1, 3);
dimensions = NaN(1, 3);
center = NaN;
footprint = NaN(4, 2);
% Graph
vertices = NaN(8, 3);
edges = [1 2; 2 3; 3 4; 4 1; % bottom square
5 6; 6 8; 8 7; 7 5; % top square
1 5; 2 6; 3 8; 4 7]; % vertical edges
% Plotting
lines;
end
methods (Access = public)
function obj = initialize(obj, bounds, tag, label)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
bounds (2, 3) double;
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
label (1, 1) string = "";
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
end
obj.tag = tag;
obj.label = label;
%% Define geometry bounds by LL corner and UR corner
obj.minCorner = bounds(1, 1:3);
obj.maxCorner = bounds(2, 1:3);
% Compute L, W, H
obj.dimensions = [obj.maxCorner(1) - obj.minCorner(1), obj.maxCorner(2) - obj.minCorner(2), obj.maxCorner(3) - obj.minCorner(3)];
% Compute center
obj.center = obj.minCorner + obj.dimensions ./ 2;
% Compute vertices
obj.vertices = [obj.minCorner;
obj.maxCorner(1), obj.minCorner(2:3);
obj.maxCorner(1:2), obj.minCorner(3);
obj.minCorner(1), obj.maxCorner(2), obj.minCorner(3);
obj.minCorner(1:2), obj.maxCorner(3);
obj.maxCorner(1), obj.minCorner(2), obj.maxCorner(3);
obj.minCorner(1), obj.maxCorner(2:3)
obj.maxCorner;];
% Compute footprint
obj.footprint = [obj.minCorner(1:2); ...
[obj.minCorner(1), obj.maxCorner(2)]; ...
[obj.maxCorner(1), obj.minCorner(2)]; ...
obj.maxCorner(1:2)];
end
function r = random(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
end
arguments (Output)
r (1, 3) double
end
r = (obj.vertices(1, 1:3) + rand(1, 3) .* obj.vertices(8, 1:3) - obj.vertices(1, 1:3))';
end
function d = distance(obj, pos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
pos (:, 3) double;
end
arguments (Output)
d (:, 1) double
end
assert(~obj.contains(pos), "Cannot determine distance for a point inside of the geometry");
cPos = NaN(1, 3);
for ii = 1:3
if pos(ii) < obj.minCorner(ii)
cPos(ii) = obj.minCorner(ii);
elseif pos(ii) > obj.maxCorner(ii)
cPos(ii) = obj.maxCorner(ii);
else
cPos(ii) = pos(ii);
end
end
d = norm(cPos - pos);
end
function d = interiorDistance(obj, pos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
pos (:, 3) double;
end
arguments (Output)
d (:, 1) double
end
assert(obj.contains(pos), "Cannot determine interior distance for a point outside of the geometry");
% find minimum distance to any face
d = min([pos(1) - obj.minCorner(1), ...
pos(2) - obj.minCorner(2), ...
pos(3) - obj.minCorner(3), ...
obj.maxCorner(1) - pos(1), ...
obj.maxCorner(2) - pos(2), ...
obj.maxCorner(3) - pos(3)]);
end
function c = contains(obj, pos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
pos (:, 3) double;
end
arguments (Output)
c (:, 1) logical
end
c = all(pos >= repmat(obj.minCorner, size(pos, 1), 1), 2) & all(pos <= repmat(obj.maxCorner, size(pos, 1), 1), 2);
end
function c = containsLine(obj, pos1, pos2)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
pos1 (1, 3) double;
pos2 (1, 3) double;
end
arguments (Output)
c (1, 1) logical
end
d = pos2 - pos1;
% edge case where the line is parallel to the geometry
if abs(d) < 1e-12
% check if it happens to start or end inside or outside of
% the geometry
if obj.contains(pos1) || obj.contains(pos2)
c = true;
else
c = false;
end
return;
end
tmin = -inf;
tmax = inf;
% Standard case
for ii = 1:3
t1 = (obj.minCorner(ii) - pos1(ii)) / d(ii);
t2 = (obj.maxCorner(ii) - pos2(ii)) / d(ii);
tmin = max(tmin, min(t1, t2));
tmax = min(tmax, max(t1, t2));
if tmin > tmax
c = false;
return;
end
end
c = (tmax >= 0) && (tmin <= 1);
end
function [obj, f] = plotWireframe(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
ind (1, :) double = NaN;
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'rectangularPrism')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
% Create axes if they don't already exist
f = firstPlotSetup(f);
% Create plotting inputs from vertices and edges
X = [obj.vertices(obj.edges(:,1),1), obj.vertices(obj.edges(:,2),1)]';
Y = [obj.vertices(obj.edges(:,1),2), obj.vertices(obj.edges(:,2),2)]';
Z = [obj.vertices(obj.edges(:,1),3), obj.vertices(obj.edges(:,2),3)]';
% Plot the boundaries of the geometry into 3D view
if isnan(ind)
o = plot3(f.CurrentAxes, X, Y, Z, '-', 'Color', obj.tag.color, 'LineWidth', 2);
else
hold(f.Children(1).Children(ind(1)), "on");
o = plot3(f.Children(1).Children(ind(1)), X, Y, Z, '-', 'Color', obj.tag.color, 'LineWidth', 2);
hold(f.Children(1).Children(ind(1)), "off");
end
% Copy to other requested tiles
if numel(ind) > 1
for ii = 2:size(ind, 2)
o = [o, copyobj(o(:, 1), f.Children(1).Children(ind(ii)))];
end
end
obj.lines = o;
end
end
end

View File

@@ -1,106 +0,0 @@
classdef rectangularPrismConstraint
% Rectangular prism constraint geometry
properties (SetAccess = private, GetAccess = public)
tag = REGION_TYPE.INVALID;
label = "";
minCorner = NaN(3, 1);
maxCorner = NaN(3, 1);
dimensions = NaN(3, 1);
center = NaN;
vertices = NaN(8, 3);
footprint = NaN(2, 4);
end
methods (Access = public)
function obj = initialize(obj, bounds, tag, label)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrismConstraint')};
bounds (3, 2) double;
tag (1, 1) REGION_TYPE = REGION_TYPE.INVALID;
label (1, 1) string = "";
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'rectangularPrismConstraint')};
end
obj.tag = tag;
obj.label = label;
%% Define geometry bounds by LL corner and UR corner
obj.minCorner = bounds(:, 1);
obj.maxCorner = bounds(:, 2);
% Compute L, W, H
obj.dimensions = [obj.maxCorner(1) - obj.minCorner(1), obj.maxCorner(2) - obj.minCorner(2), obj.maxCorner(3) - obj.minCorner(3)];
% Compute center
obj.center = obj.minCorner + obj.dimensions ./ 2;
% Compute vertices
obj.vertices = [obj.minCorner';
obj.maxCorner(1), obj.minCorner(2:3)';
obj.maxCorner(1:2)', obj.minCorner(3);
obj.minCorner(1), obj.maxCorner(2), obj.minCorner(3);
obj.minCorner(1:2)', obj.maxCorner(3);
obj.maxCorner(1), obj.minCorner(2), obj.maxCorner(3);
obj.minCorner(1), obj.maxCorner(2:3)'
obj.maxCorner';];
% Compute footprint
obj.footprint = [obj.minCorner(1:2, 1), ...
[obj.minCorner(1, 1); obj.maxCorner(2, 1)], ...
[obj.maxCorner(1, 1); obj.minCorner(2, 1)], ...
obj.maxCorner(1:2, 1)];
end
function r = random(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrismConstraint')};
end
arguments (Output)
r (1, 3) double
end
r = (obj.vertices(1, 1:3) + rand(1, 3) .* obj.vertices(8, 1:3) - obj.vertices(1, 1:3))';
end
function c = contains(obj, pos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrismConstraint')};
pos (:, 3) double;
end
arguments (Output)
c (1, 1) logical
end
c = all(pos >= repmat(obj.minCorner', size(pos, 1), 1), 2) & all(pos <= repmat(obj.maxCorner', size(pos, 1), 1), 2);
end
function f = plotWireframe(obj, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'rectangularPrismConstraint')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
% Create axes if they don't already exist
f = firstPlotSetup(f);
edges = [1 2; 2 3; 3 4; 4 1; % bottom square
5 6; 6 8; 8 7; 7 5; % top square
1 5; 2 6; 3 8; 4 7]; % vertical edges
% Create plotting inputs from vertices and edges
X = [obj.vertices(edges(:,1),1), obj.vertices(edges(:,2),1)]';
Y = [obj.vertices(edges(:,1),2), obj.vertices(edges(:,2),2)]';
Z = [obj.vertices(edges(:,1),3), obj.vertices(edges(:,2),3)]';
% Plot the boundaries of the constraint geometry
hold(f.CurrentAxes, "on");
plot3(X, Y, Z, '-', 'Color', obj.tag.color, 'LineWidth', 2);
hold(f.CurrentAxes, "off");
end
end
end

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@@ -0,0 +1,26 @@
function nextPos = gradientAscent(sensedValues, sensedPositions, pos, rate)
arguments (Input)
sensedValues (:, 1) double;
sensedPositions (:, 3) double;
pos (1, 3) double;
rate (1, 1) double = 0.1;
end
arguments (Output)
nextPos(1, 3) double;
end
% As a default, maintain current position
if size(sensedValues, 1) == 0 && size(sensedPositions, 1) == 0
nextPos = pos;
return;
end
% Select next position by maximum sensed value
nextPos = sensedPositions(sensedValues == max(sensedValues), :);
nextPos = [nextPos(1, 1:2), pos(3)]; % just in case two get selected, simply pick one
% rate-limit motion
v = nextPos - pos;
nextPos = pos + (v / norm(v, 2)) * rate;
end

343
miSim.m
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@@ -3,37 +3,352 @@ classdef miSim
% Simulation parameters
properties (SetAccess = private, GetAccess = public)
domain = rectangularPrismConstraint;
timestep = NaN; % delta time interval for simulation iterations
partitioningFreq = NaN; % number of simulation timesteps at which the partitioning routine is re-run
maxIter = NaN; % maximum number of simulation iterations
domain = rectangularPrism;
objective = sensingObjective;
constraintGeometries = cell(0, 1); % geometries that define constraints within the domain
obstacles = cell(0, 1); % geometries that define obstacles within the domain
agents = cell(0, 1); % agents that move within the domain
adjacency = NaN; % Adjacency matrix representing communications network graph
partitioning = NaN;
end
properties (Access = private)
% Plot objects
connectionsPlot; % objects for lines connecting agents in spatial plots
graphPlot; % objects for abstract network graph plot
partitionPlot; % objects for partition plot
% Indicies for various plot types in the main tiled layout figure
spatialPlotIndices = [6, 4, 3, 2];
objectivePlotIndices = [6, 4];
networkGraphIndex = 5;
partitionGraphIndex = 1;
end
methods (Access = public)
function obj = initialize(obj, domain, objective, agents, constraintGeometries)
function [obj, f] = initialize(obj, domain, objective, agents, timestep, partitoningFreq, maxIter, obstacles)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
domain (1, 1) {mustBeConstraintGeometries};
domain (1, 1) {mustBeGeometry};
objective (1, 1) {mustBeA(objective, 'sensingObjective')};
agents (:, 1) cell {mustBeAgents};
constraintGeometries (:, 1) cell {mustBeConstraintGeometries} = cell(0, 1);
agents (:, 1) cell;
timestep (:, 1) double = 0.05;
partitoningFreq (:, 1) double = 0.25
maxIter (:, 1) double = 1000;
obstacles (:, 1) cell {mustBeGeometry} = cell(0, 1);
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
% Define simulation time parameters
obj.timestep = timestep;
obj.maxIter = maxIter;
% Define domain
obj.domain = domain;
obj.partitioningFreq = partitoningFreq;
% Add geometries representing obstacles within the domain
obj.obstacles = obstacles;
% Define objective
obj.objective = objective;
% Define agents
obj.agents = agents;
% Compute adjacency matrix
obj = obj.updateAdjacency();
% Create initial partitioning
obj = obj.partition();
% Set up initial plot
% Set up axes arrangement
% Plot domain
[obj.domain, f] = obj.domain.plotWireframe(obj.spatialPlotIndices);
% Plot obstacles
for ii = 1:size(obj.obstacles, 1)
[obj.obstacles{ii}, f] = obj.obstacles{ii}.plotWireframe(obj.spatialPlotIndices, f);
end
% Plot objective gradient
f = obj.objective.plot(obj.objectivePlotIndices, f);
% Plot agents and their collision geometries
for ii = 1:size(obj.agents, 1)
[obj.agents{ii}, f] = obj.agents{ii}.plot(obj.spatialPlotIndices, f);
end
% Plot communication links
[obj, f] = obj.plotConnections(obj.spatialPlotIndices, f);
% Plot abstract network graph
[obj, f] = obj.plotGraph(obj.networkGraphIndex, f);
% Plot domain partitioning
[obj, f] = obj.plotPartitions(obj.partitionGraphIndex, f);
end
function [obj, f] = run(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
% Create axes if they don't already exist
f = firstPlotSetup(f);
% Set up times to iterate over
times = linspace(0, obj.timestep * obj.maxIter, obj.maxIter+1)';
partitioningTimes = times(obj.partitioningFreq:obj.partitioningFreq:size(times, 1));
% Start video writer
v = setupVideoWriter(obj.timestep);
v.open();
for ii = 1:size(times, 1)
% Display current sim time
t = times(ii);
fprintf("Sim Time: %4.2f (%d/%d)\n", t, ii, obj.maxIter)
% Check if it's time for new partitions
updatePartitions = false;
if ismember(t, partitioningTimes)
updatePartitions = true;
obj = obj.partition();
end
% Iterate over agents to simulate their motion
for jj = 1:size(obj.agents, 1)
obj.agents{jj} = obj.agents{jj}.run(obj.objective, obj.domain, obj.partitioning);
end
% Update adjacency matrix
obj = obj.updateAdjacency;
% Update plots
[obj, f] = obj.updatePlots(f, updatePartitions);
% Write frame in to video
I = getframe(f);
v.writeVideo(I);
end
% Close video file
v.close();
end
function obj = partition(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
%% Define domain
obj.domain = domain;
% Assess sensing performance of each agent at each sample point
% in the domain
agentPerformances = cellfun(@(x) reshape(x.sensorModel.sensorPerformance(x.pos, x.pan, x.tilt, [obj.objective.X(:), obj.objective.Y(:), zeros(size(obj.objective.X(:)))]), size(obj.objective.X)), obj.agents, 'UniformOutput', false);
agentPerformances = cat(3, agentPerformances{:});
%% Add constraint geometries against the domain
obj.constraintGeometries = constraintGeometries;
% Get highest performance value at each point
[~, idx] = max(agentPerformances, [], 3);
%% Define objective
obj.objective = objective;
% Collect agent indices in the same way
agentInds = cellfun(@(x) x.index * ones(size(obj.objective.X)), obj.agents, 'UniformOutput', false);
agentInds = cat(3, agentInds{:});
%% Define agents
obj.agents = agents;
% Get highest performing agent's index
[m,n,~] = size(agentInds);
[i,j] = ndgrid(1:m, 1:n);
obj.partitioning = agentInds(sub2ind(size(agentInds), i, j, idx));
end
function [obj, f] = updatePlots(obj, f, updatePartitions)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
updatePartitions (1, 1) logical = false;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
f (1, 1) {mustBeA(f, 'matlab.ui.Figure')};
end
% Update agent positions, collision geometries
for ii = 1:size(obj.agents, 1)
obj.agents{ii}.updatePlots();
end
% The remaining updates might be possible to do in a clever way
% that moves existing lines instead of clearing and
% re-plotting, which is much better for performance boost
% Update agent connections plot
delete(obj.connectionsPlot);
[obj, f] = obj.plotConnections(obj.spatialPlotIndices, f);
% Update network graph plot
delete(obj.graphPlot);
[obj, f] = obj.plotGraph(obj.networkGraphIndex, f);
% Update partitioning plot
if updatePartitions
delete(obj.partitionPlot);
[obj, f] = obj.plotPartitions(obj.partitionGraphIndex, f);
end
% reset plot limits to fit domain
for ii = 1:size(obj.spatialPlotIndices, 2)
xlim(f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(1), obj.domain.maxCorner(1)]);
ylim(f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(2), obj.domain.maxCorner(2)]);
zlim(f.Children(1).Children(obj.spatialPlotIndices(ii)), [obj.domain.minCorner(3), obj.domain.maxCorner(3)]);
end
drawnow;
end
function obj = updateAdjacency(obj)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'miSim')};
end
% Initialize assuming only self-connections
A = logical(eye(size(obj.agents, 1)));
% Check lower triangle off-diagonal connections
for ii = 2:size(A, 1)
for jj = 1:(ii - 1)
if norm(obj.agents{ii}.pos - obj.agents{jj}.pos) <= min([obj.agents{ii}.comRange, obj.agents{jj}.comRange])
% Make sure that obstacles don't obstruct the line
% of sight, breaking the connection
for kk = 1:size(obj.obstacles, 1)
if ~obj.obstacles{kk}.containsLine(obj.agents{ii}.pos, obj.agents{jj}.pos)
A(ii, jj) = true;
end
end
% need extra handling for cases with no obstacles
if isempty(obj.obstacles)
A(ii, jj) = true;
end
end
end
end
obj.adjacency = A | A';
end
function [obj, f] = plotConnections(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
ind (1, :) double = NaN;
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
% Iterate over lower triangle off-diagonal region of the
% adjacency matrix to plot communications links between agents
X = []; Y = []; Z = [];
for ii = 2:size(obj.adjacency, 1)
for jj = 1:(ii - 1)
if obj.adjacency(ii, jj)
X = [X; obj.agents{ii}.pos(1), obj.agents{jj}.pos(1)];
Y = [Y; obj.agents{ii}.pos(2), obj.agents{jj}.pos(2)];
Z = [Z; obj.agents{ii}.pos(3), obj.agents{jj}.pos(3)];
end
end
end
X = X'; Y = Y'; Z = Z';
% Plot the connections
if isnan(ind)
hold(f.CurrentAxes, "on");
o = plot3(f.CurrentAxes, X, Y, Z, 'Color', 'g', 'LineWidth', 2, 'LineStyle', '--');
hold(f.CurrentAxes, "off");
else
hold(f.Children(1).Children(ind(1)), "on");
o = plot3(f.Children(1).Children(ind(1)), X, Y, Z, 'Color', 'g', 'LineWidth', 2, 'LineStyle', '--');
hold(f.Children(1).Children(ind(1)), "off");
end
% Copy to other plots
if size(ind, 2) > 1
for ii = 2:size(ind, 2)
o = [o, copyobj(o(:, 1), f.Children(1).Children(ind(ii)))];
end
end
obj.connectionsPlot = o;
end
function [obj, f] = plotPartitions(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
ind (1, :) double = NaN;
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
if isnan(ind)
hold(f.CurrentAxes, 'on');
o = imagesc(f.CurrentAxes, obj.partitioning);
hold(f.CurrentAxes, 'off');
else
hold(f.Children(1).Children(ind(1)), 'on');
o = imagesc(f.Children(1).Children(ind(1)), obj.partitioning);
hold(f.Children(1).Children(ind(1)), 'on');
if size(ind, 2) > 1
for ii = 2:size(ind, 2)
o = [o, copyobj(o(1), f.Children(1).Children(ind(ii)))];
end
end
end
obj.partitionPlot = o;
end
function [obj, f] = plotGraph(obj, ind, f)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'miSim')};
ind (1, :) double = NaN;
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');
% Plot graph object
if isnan(ind)
hold(f.CurrentAxes, 'on');
o = plot(f.CurrentAxes, G, 'LineStyle', '--', 'EdgeColor', 'g', 'NodeColor', 'k', 'LineWidth', 2);
hold(f.CurrentAxes, 'off');
else
hold(f.Children(1).Children(ind(1)), 'on');
o = plot(f.Children(1).Children(ind(1)), G, 'LineStyle', '--', 'EdgeColor', 'g', 'NodeColor', 'k', 'LineWidth', 2);
hold(f.Children(1).Children(ind(1)), 'off');
if size(ind, 2) > 1
for ii = 2:size(ind, 2)
o = [o; copyobj(o(1), f.Children(1).Children(ind(ii)))];
end
end
end
obj.graphPlot = o;
end
end

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@@ -0,0 +1,2 @@
<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="sensingModels" Type="Relative"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="420d04e4-3880-4a45-8609-11cb30d87302" type="Reference"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="guidanceModels" Type="Relative"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1d8d2b42-2863-4985-9cf2-980917971eba" type="Reference"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="sandbox" Type="Relative"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="ff13e617-a2ad-49b1-a9b5-668ac2cffc4a" type="Reference"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info Ref="validators/arguments" Type="Relative"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="b7c7eec5-a318-4c17-adb2-b13a21bf0609" type="Reference"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="mustBeGeometry.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="mustBeSensor.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="domainContainsObstacle.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="obstacleCoversObjective.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="arguments" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="mustBeConstraintGeometries.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="obstacleCrowdsObjective.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="agentsCrowdObjective.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="rectangularPrism.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="rectangularPrismConstraint.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="cone.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="setupVideoWriter.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="sandbox" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="sensingModels" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="guidanceModels" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="sigmoidSensor.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="fixedCardinalSensor.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info>
<Category UUID="FileClassCategory">
<Label UUID="design"/>
</Category>
</Info>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="gradientAscent.m" type="File"/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info/>

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<?xml version="1.0" encoding="UTF-8"?>
<Info location="1" type="DIR_SIGNIFIER"/>

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classdef fixedCardinalSensor
% Senses in the +/-x, +/- y directions at some specified fixed length
properties
r = 0.1; % fixed sensing length
end
methods (Access = public)
function obj = initialize(obj, r)
arguments(Input)
obj (1, 1) {mustBeA(obj, 'fixedCardinalSensor')};
r (1, 1) double;
end
arguments(Output)
obj (1, 1) {mustBeA(obj, 'fixedCardinalSensor')};
end
obj.r = r;
end
function [neighborValues, neighborPos] = sense(obj, agent, sensingObjective, domain, partitioning)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'fixedCardinalSensor')};
agent (1, 1) {mustBeA(agent, 'agent')};
sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
domain (1, 1) {mustBeGeometry};
partitioning (:, :) double = NaN;
end
arguments (Output)
neighborValues (4, 1) double;
neighborPos (4, 3) double;
end
% Evaluate objective at position offsets +/-[r, 0, 0] and +/-[0, r, 0]
currentPos = agent.pos(1:2);
neighborPos = [currentPos(1) + obj.r, currentPos(2); ... % (+x)
currentPos(1), currentPos(2) + obj.r; ... % (+y)
currentPos(1) - obj.r, currentPos(2); ... % (-x)
currentPos(1), currentPos(2) - obj.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(agent.pos, sum(outOfBounds), 1);
% Sense values at selected positions
neighborValues = [sensingObjective.objectiveFunction(neighborPos(1, 1), neighborPos(1, 2)), ... % (+x)
sensingObjective.objectiveFunction(neighborPos(2, 1), neighborPos(2, 2)), ... % (+y)
sensingObjective.objectiveFunction(neighborPos(3, 1), neighborPos(3, 2)), ... % (-x)
sensingObjective.objectiveFunction(neighborPos(4, 1), neighborPos(4, 2)), ... % (-y)
];
% Prevent out of bounds locations from ever possibly being selected
neighborValues(outOfBounds) = 0;
end
function value = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'fixedCardinalSensor')};
agentPos (1, 3) double;
agentPan (1, 1) double;
agentTilt (1, 1) double;
targetPos (:, 3) double;
end
arguments (Output)
value (:, 1) double;
end
value = 0.5 * ones(size(targetPos, 1), 1);
end
end
end

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@@ -0,0 +1,83 @@
classdef sigmoidSensor
properties (SetAccess = private, GetAccess = public)
% Sensor parameters
alphaDist = NaN;
betaDist = NaN;
alphaPan = NaN;
betaPan = NaN;
alphaTilt = NaN;
betaTilt = NaN;
r = NaN;
end
methods (Access = public)
function obj = initialize(obj, alphaDist, betaDist, alphaPan, betaPan, alphaTilt, betaTilt)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'sigmoidSensor')}
alphaDist (1, 1) double;
betaDist (1, 1) double;
alphaPan (1, 1) double;
betaPan (1, 1) double;
alphaTilt (1, 1) double;
betaTilt (1, 1) double;
end
arguments (Output)
obj (1, 1) {mustBeA(obj, 'sigmoidSensor')}
end
obj.alphaDist = alphaDist;
obj.betaDist = betaDist;
obj.alphaPan = alphaPan;
obj.betaPan = betaPan;
obj.alphaTilt = alphaTilt;
obj.betaTilt = betaTilt;
obj.r = obj.alphaDist;
end
function [values, positions] = sense(obj, agent, sensingObjective, domain, partitioning)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'sigmoidSensor')};
agent (1, 1) {mustBeA(agent, 'agent')};
sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
domain (1, 1) {mustBeGeometry};
partitioning (:, :) double;
end
arguments (Output)
values (:, 1) double;
positions (:, 3) double;
end
% Find positions for this agent's assigned partition in the domain
idx = partitioning == agent.index;
positions = [sensingObjective.X(idx), sensingObjective.Y(idx), zeros(size(sensingObjective.X(idx)))];
% Evaluate objective function at every point in this agent's
% assigned partiton
values = sensingObjective.values(idx);
end
function value = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos)
arguments (Input)
obj (1, 1) {mustBeA(obj, 'sigmoidSensor')};
agentPos (1, 3) double;
agentPan (1, 1) double;
agentTilt (1, 1) double;
targetPos (:, 3) double;
end
arguments (Output)
value (:, 1) double;
end
d = vecnorm(agentPos - targetPos, 2, 2);
panAngle = atan2(targetPos(:, 2) - agentPos(2), targetPos(:, 1) - agentPos(1)) - agentPan;
tiltAngle = atan2(targetPos(:, 3) - agentPos(3), d) - agentTilt;
% Membership functions
mu_d = 1 - (1 ./ (1 + exp(-obj.betaDist .* (d - obj.alphaDist)))); % distance
mu_p = (1 ./ (1 + exp(-obj.betaPan .* (panAngle + obj.alphaPan)))) - (1 ./ (1 + exp(-obj.betaPan .* (panAngle - obj.alphaPan)))); % pan
mu_t = (1 ./ (1 + exp(-obj.betaPan .* (tiltAngle + obj.alphaPan)))) - (1 ./ (1 + exp(-obj.betaPan .* (tiltAngle - obj.alphaPan)))); % tilt
value = mu_d .* mu_p .* mu_t;
end
end
end

View File

@@ -16,7 +16,7 @@ classdef sensingObjective
arguments (Input)
obj (1,1) {mustBeA(obj, 'sensingObjective')};
objectiveFunction (1, 1) {mustBeA(objectiveFunction, 'function_handle')};
footprint (2, :) double;
footprint (:, 2) double;
groundAlt (1, 1) double = 0;
discretizationStep (1, 1) double = 1;
end
@@ -27,10 +27,10 @@ classdef sensingObjective
obj.groundAlt = groundAlt;
% Extract footprint limits
xMin = min(footprint(1, :));
xMax = max(footprint(1, :));
yMin = min(footprint(2, :));
yMax = max(footprint(2, :));
xMin = min(footprint(:, 1));
xMax = max(footprint(:, 1));
yMin = min(footprint(:, 2));
yMax = max(footprint(:, 2));
xGrid = unique([xMin:discretizationStep:xMax, xMax]);
yGrid = unique([yMin:discretizationStep:yMax, yMax]);
@@ -46,9 +46,10 @@ classdef sensingObjective
idx = obj.values == max(obj.values, [], "all");
obj.groundPos = [obj.X(idx), obj.Y(idx)];
end
function f = plot(obj, f)
function f = plot(obj, ind, f)
arguments (Input)
obj (1,1) {mustBeA(obj, 'sensingObjective')};
ind (1, :) double = NaN;
f (1,1) {mustBeA(f, 'matlab.ui.Figure')} = figure;
end
arguments (Output)
@@ -59,11 +60,27 @@ classdef sensingObjective
f = firstPlotSetup(f);
% Plot gradient on the "floor" of the domain
if isnan(ind)
hold(f.CurrentAxes, "on");
s = surf(obj.X, obj.Y, repmat(obj.groundAlt, size(obj.X)), obj.values ./ max(obj.values, [], "all"), 'EdgeColor', 'none');
s.HitTest = 'off';
s.PickableParts = 'none';
o = surf(f.CurrentAxes, obj.X, obj.Y, repmat(obj.groundAlt, size(obj.X)), obj.values ./ max(obj.values, [], "all"), 'EdgeColor', 'none');
o.HitTest = 'off';
o.PickableParts = 'none';
hold(f.CurrentAxes, "off");
else
hold(f.Children(1).Children(ind(1)), "on");
o = surf(f.Children(1).Children(ind(1)), obj.X, obj.Y, repmat(obj.groundAlt, size(obj.X)), obj.values ./ max(obj.values, [], "all"), 'EdgeColor', 'none');
o.HitTest = 'off';
o.PickableParts = 'none';
hold(f.Children(1).Children(ind(1)), "off");
end
% Add to other perspectives
if size(ind, 2) > 1
for ii = 2:size(ind, 2)
copyobj(o, f.Children(1).Children(ind(ii)));
end
end
end
end
end

17
setupVideoWriter.m Normal file
View File

@@ -0,0 +1,17 @@
function v = setupVideoWriter(timestep)
arguments (Input)
timestep (1, 1) double;
end
arguments (Output)
v (1, 1) {mustBeA(v, 'VideoWriter')};
end
if ispc || ismac
v = VideoWriter(fullfile('sandbox', strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'), '_miSimHist')), 'MPEG-4');
elseif isunix
v = VideoWriter(fullfile('sandbox', strcat(string(datetime('now'), 'yyyy_MM_dd_HH_mm_ss'), '_miSimHist')), 'Motion JPEG AVI');
end
v.FrameRate = 1/timestep;
v.Quality = 90;
end

View File

@@ -1,51 +1,76 @@
classdef test_miSim < matlab.unittest.TestCase
properties (Access = private)
testClass = miSim;
% Domain
domain = rectangularPrismConstraint;
domain = rectangularPrism; % domain geometry
maxIter = 250;
timestep = 0.05
partitoningFreq = 5;
% Obstacles
constraintGeometries = cell(1, 0);
minNumObstacles = 1; % Minimum number of obstacles to be randomly generated
maxNumObstacles = 3; % Maximum number of obstacles to be randomly generated
minObstacleSize = 1; % Minimum size of a randomly generated obstacle
maxObstacleSize = 6; % Maximum size of a randomly generated obstacle
obstacles = cell(1, 0);
% Objective
objectiveDiscretizationStep = 0.01; % Step at which the objective function is solved in X and Y space
protectedRange = 1; % Minimum distance between the sensing objective and the edge of the domain
objective = sensingObjective;
objectiveFunction = @(x, y) 0;
objectiveDiscretizationStep = 0.01;
% Agents
minAgents = 3;
maxAgents = 9;
agents = cell(1, 0);
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
minCollisionRange = 0.1;
maxCollisionRange = 0.5;
minCollisionRange = 0.1; % Minimum randomly generated collision geometry size
maxCollisionRange = 0.5; % Maximum randomly generated collision geometry size
collisionRanges = NaN;
% Communications
comRange = 5;
comRange = 5; % Maximum range between agents that forms a communications link
end
% Setup for each test
methods (TestMethodSetup)
% Generate a random domain
function tc = setDomain(tc)
% random integer-sized domain within [-10, 10] in all dimensions
tc.domain = tc.domain.initialize(ceil([rand * -10, rand * 10; rand * -10, rand * 10; rand * -10, rand * 10]), REGION_TYPE.DOMAIN, "Domain");
% random integer-sized cube domain ranging from [0, 5 -> 25]
% in all dimensions
L = ceil(5 + rand * 10 + rand * 10);
tc.domain = tc.domain.initialize([zeros(1, 3); L * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
end
% Generate a random sensing objective within that domain
function tc = setSensingObjective(tc)
% Using a bivariate normal distribution
% Set peak position (mean)
mu = tc.domain.minCorner;
while tc.domain.interiorDistance(mu) < tc.protectedRange
mu = tc.domain.random();
sig = [3, 1; 1, 4];
tc.objectiveFunction = @(x, y) mvnpdf([x(:), y(:)], mu(1, 1:2), sig);
tc.objective = tc.objective.initialize(tc.objectiveFunction, tc.domain.footprint, tc.domain.minCorner(3, 1), tc.objectiveDiscretizationStep);
end
% Instantiate agents, they will be initialized under different
% parameters in individual test cases
mu(3) = 0;
% Set standard deviations of bivariate distribution
sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
% Define objective
tc.objective = tc.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], mu(1:2), sig), tc.domain.footprint, tc.domain.minCorner(3), tc.objectiveDiscretizationStep);
end
% Instantiate agents
function tc = setAgents(tc)
% Agents will be initialized under different parameters in
% individual test cases
% Instantiate a random number of agents according to parameters
for ii = 1:randi([tc.minAgents, tc.maxAgents])
tc.agents{ii, 1} = agent;
end
% Define random collision ranges for each agent
tc.collisionRanges = tc.minCollisionRange + rand(size(tc.agents, 1), 1) * (tc.maxCollisionRange - tc.minCollisionRange);
end
end
@@ -53,149 +78,371 @@ classdef test_miSim < matlab.unittest.TestCase
methods (Test)
% Test methods
function misim_initialization(tc)
% randomly create 2-3 constraint geometries
nGeom = 1 + randi(2);
tc.constraintGeometries = cell(nGeom, 1);
for ii = 1:size(tc.constraintGeometries, 1)
% Instantiate a rectangular prism constraint that spans the
% domain's height
tc.constraintGeometries{ii, 1} = rectangularPrismConstraint;
% randomly create obstacles
nGeom = tc.minNumObstacles + randi(tc.maxNumObstacles - tc.minNumObstacles);
tc.obstacles = cell(nGeom, 1);
% Randomly come up with constraint geometries until they
% fit within the domain
candidateMinCorner = -Inf(3, 1);
candidateMaxCorner = Inf(3, 1);
% 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;
% make sure the obstacles don't contain the sensing objective
obstructs = true;
while obstructs
% Randomly generate min corner for the obstacle
candidateMinCorner = tc.domain.random();
candidateMinCorner = [candidateMinCorner(1:2), 0]; % bind obstacles to floor of domain
% Make sure the obstacle is in the domain
while any(candidateMinCorner(1:2, 1) < tc.domain.minCorner(1:2, 1))
candidateMinCorner = tc.domain.minCorner(1:3, 1) + [(tc.domain.maxCorner(1:2, 1) - tc.domain.minCorner(1:2, 1)) .* rand(2, 1); -Inf]; % random spots on the ground
% 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
while any(candidateMaxCorner(1:2, 1) > tc.domain.maxCorner(1:2, 1))
candidateMaxCorner = [candidateMinCorner(1:2, 1); 0] + [(tc.domain.maxCorner(1:2, 1) - tc.domain.minCorner(1:2, 1)) .* rand(2, 1) ./ 2; Inf]; % halved to keep from being excessively large
end
if violation
continue;
end
% once a domain-valid obstacle has been found, make
% sure it doesn't obstruct the sensing target
if all(candidateMinCorner(1:2, 1)' <= tc.objective.groundPos) && all(candidateMaxCorner(1:2, 1)' >= tc.objective.groundPos)
% reset to try again
candidateMinCorner = -Inf(3, 1);
candidateMaxCorner = Inf(3, 1);
else
obstructs = false;
% 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
% Reduce infinite dimensions to the domain
candidateMinCorner(isinf(candidateMinCorner)) = tc.domain.minCorner(isinf(candidateMinCorner));
candidateMaxCorner(isinf(candidateMaxCorner)) = tc.domain.maxCorner(isinf(candidateMaxCorner));
% Initialize constraint geometry
tc.constraintGeometries{ii, 1} = tc.constraintGeometries{ii, 1}.initialize([candidateMinCorner, candidateMaxCorner], REGION_TYPE.OBSTACLE, sprintf("Column obstacle %d", ii));
end
% Repeat this until a connected set of agent initial conditions
% is found by random chance
connected = false;
while ~connected
% Randomly place agents in the domain
% Add agents individually, ensuring that each addition does not
% invalidate the initialization setup
for ii = 1:size(tc.agents, 1)
posInvalid = true;
while posInvalid
% Initialize the agent into a random spot in the domain
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();
candidateGeometry = rectangularPrismConstraint;
tc.agents{ii, 1} = tc.agents{ii, 1}.initialize(candidatePos, zeros(1, 3), eye(3), candidateGeometry.initialize([candidatePos - tc.collisionRanges(ii, 1) * ones(1, 3); candidatePos + tc.collisionRanges(ii, 1) * ones(1, 3)]', REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", ii)), ii, sprintf("Agent %d", ii));
% Check obstacles to confirm that none are violated
for jj = 1:size(tc.constraintGeometries, 1)
inside = false;
if tc.constraintGeometries{jj, 1}.contains(tc.agents{ii, 1}.pos)
% Found a violation, stop checking
inside = true;
break;
end
else
candidatePos = tc.agents{randi(ii - 1)}.pos + sign(randn([1, 3])) .* (rand(1, 3) .* tc.comRange/sqrt(2));
end
% Agent is inside obstacle, try again
if inside
% Make sure that the candidate position is within the
% domain
if ~tc.domain.contains(candidatePos)
continue;
end
% Create a collision geometry for this agent
candidateGeometry = rectangularPrismConstraint;
candidateGeometry = candidateGeometry.initialize([tc.agents{ii, 1}.pos - 0.1 * ones(1, 3); tc.agents{ii, 1}.pos + 0.1 * ones(1, 3)]', REGION_TYPE.COLLISION, sprintf("Agent %d collision volume", ii));
% 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
% Check previously placed agents for collisions
% 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)
% Check if previously defined agents collide with
% this one
colliding = false;
if candidateGeometry.contains(tc.agents{jj, 1}.pos)
% Found a violation, stop checking
colliding = true;
break;
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
% Agent is colliding with another, try again
if ii ~= 1 && colliding
% New agent must be connected to an existing agent to
% be valid
if ii ~= 1 && ~any(connections)
continue;
end
% Allow to proceed since no obstacle/collision
% violations were found
posInvalid = false;
% Initialize candidate agent collision geometry
candidateGeometry = rectangularPrism;
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));
% Initialize candidate agent sensor model
sensor = fixedCardinalSensor;
sensor = sensor.initialize(tc.sensingLength);
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, 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
% Collect all agent positions
posArray = arrayfun(@(x) x{1}.pos, tc.agents, 'UniformOutput', false);
posArray = reshape([posArray{:}], size(tc.agents, 1), 3);
% Communications checks
adjacency = false(size(tc.agents, 1), size(tc.agents, 1));
for ii = 1:size(tc.agents, 1)
% Compute distance from each to all agents
for jj = 1:(size(tc.agents, 1))
if norm(posArray(ii, 1:3) - posArray(jj, 1:3)) <= tc.comRange
adjacency(ii, jj) = true;
% 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
% Check connectivity
G = graph(adjacency);
connected = all(conncomp(G) == 1);
% 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
% Initialize the simulation
tc.testClass = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.constraintGeometries);
[tc.testClass, f] = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.timestep, tc.partitoningFreq, 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) - 0.5, tc.testClass.domain.maxCorner(1) + 0.5]);
ylim([tc.testClass.domain.minCorner(2) - 0.5, tc.testClass.domain.maxCorner(2) + 0.5]);
zlim([tc.testClass.domain.minCorner(3) - 0.5, tc.testClass.domain.maxCorner(3) + 0.5]);
% Randomly generate min corner for the obstacle
candidateMinCorner = tc.domain.random();
candidateMinCorner = [candidateMinCorner(1:2), 0]; % bind obstacles to floor of domain
% Plot constraint geometries
for ii = 1:size(tc.testClass.constraintGeometries, 1)
tc.testClass.constraintGeometries{ii, 1}.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
% Plot objective gradient
f = tc.testClass.objective.plot(f);
% Plot agents and their collision geometries
for ii = 1:size(tc.testClass.agents, 1)
f = tc.testClass.agents{ii, 1}.plot(f);
f = tc.testClass.agents{ii, 1}.collisionGeometry.plotWireframe(f);
% 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
% 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
% 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 collision geometry
candidateGeometry = rectangularPrism;
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));
% Initialize candidate agent sensor model
sensor = sigmoidSensor;
sensor = sensor.initialize(1, 1, 1, 1, 1, 1);
% Initialize candidate agent
newAgent = tc.agents{ii}.initialize(candidatePos, zeros(1,3), 0, 0, candidateGeometry, sensor, @gradientAscent, 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
% Initialize the simulation
[tc.testClass, f] = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter, tc.obstacles);
% Run simulation loop
[tc.testClass, f] = tc.testClass.run(f);
end
function test_basic_partitioning(tc)
% place agents a fixed distance +/- X from the domain's center
d = 1;
% make basic domain
tc.domain = tc.domain.initialize([zeros(1, 3); 10 * ones(1, 3)], REGION_TYPE.DOMAIN, "Domain");
% make basic sensing objective
tc.objective = tc.objective.initialize(@(x, y) mvnpdf([x(:), y(:)], tc.domain.center(1:2), eye(2)), tc.domain.footprint, tc.domain.minCorner(3), tc.objectiveDiscretizationStep);
% Initialize agent collision geometry
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));
% Initialize agent sensor model
sensor = sigmoidSensor;
sensor = sensor.initialize(1, 1, 1, 1, 1, 1);
% 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));
% Initialize the simulation
[tc.testClass, f] = tc.testClass.initialize(tc.domain, tc.objective, tc.agents, tc.timestep, tc.partitoningFreq, tc.maxIter);
end
end
end

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function c = agentsCrowdObjective(objective, positions, protectedRange)
arguments (Input)
objective (1, 1) {mustBeA(objective, 'sensingObjective')};
positions (:, 3) double; % this could be expanded to handle n obstacles in 1 call
protectedRange (1, 1) double;
end
arguments (Output)
c (:, 1) logical;
end
c = vecnorm(positions(:, 1:2) - objective.groundPos, 2, 2) <= protectedRange;
end

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function mustBeGeometry(geometry)
validGeometries = ["rectangularPrism";];
if isa(geometry, 'cell')
for ii = 1:size(geometry, 1)
assert(any(arrayfun(@(x) isa(geometry{ii}, x), validGeometries)), "Geometry in index %d is not a valid geometry class", ii);
end
else
assert(any(arrayfun(@(x) isa(geometry, x), validGeometries)), "Geometry is not a valid geometry class");
end
end

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function mustBeSensor(sensorModel)
validSensorModels = ["fixedCardinalSensor"; "sigmoidSensor";];
if isa(sensorModel, 'cell')
for ii = 1:size(sensorModel, 1)
assert(any(arrayfun(@(x) isa(sensorModel{ii}, x), validSensorModels)), "Sensor in index %d is not a valid sensor class", ii);
end
else
assert(any(arrayfun(@(x) isa(sensorModel, x), validSensorModels)), "Sensor is not a valid sensor class");
end
end

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function c = domainContainsObstacle(domain, obstacle)
arguments (Input)
domain (1, 1) {mustBeGeometry};
obstacle (1, 1) {mustBeGeometry}; % this could be expanded to handle n obstacles in 1 call
end
arguments (Output)
c (1, 1) logical;
end
switch class(domain)
case 'rectangularPrism'
switch class(obstacle)
case 'rectangularPrism'
c = all(domain.minCorner <= obstacle.minCorner) && all(domain.maxCorner >= obstacle.maxCorner);
otherwise
error("%s not implemented for obstacles of class %s", coder.mfunctionname, class(domain));
end
otherwise
error("%s not implemented for domains of class %s", coder.mfunctionname, class(domain));
end
end

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function c = geometryIntersects(g1, g2)
c = false;
% Check if g2 contains g1
for jj = 1:size(g1.edges, 1)
if g2.containsLine(g1.vertices(g1.edges(jj, 1), 1:3), g1.vertices(g1.edges(jj, 2), 1:3))
c = true;
return;
end
end
% Check if g1 contains g2
for jj = 1:size(g2.edges, 1)
if g1.containsLine(g2.vertices(g2.edges(jj, 1), 1:3), g2.vertices(g2.edges(jj, 2), 1:3))
c = true;
return;
end
end
end

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function mustBeAgents(agents)
validGeometries = ["rectangularPrismConstraint";];
if isa(agents, 'cell')
for ii = 1:size(agents, 1)
assert(isa(agents{ii}, "agent"), "Agent in index %d is not a valid agent class", ii);
end
else
assert(isa(agents, validGeometries), "Agent is not a valid agent class");
end
end

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function mustBeConstraintGeometries(constraintGeometry)
validGeometries = ["rectangularPrismConstraint";];
if isa(constraintGeometry, 'cell')
for ii = 1:size(constraintGeometry, 1)
assert(isa(constraintGeometry{ii}, validGeometries), "Constraint geometry in index %d is not a valid constraint geometry class", ii);
end
else
assert(isa(constraintGeometry, validGeometries), "Constraint geometry is not a valid constraint geometry class");
end
end

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function mustBeDcm(dcm)
% Assert 2D
assert(numel(size(dcm)) == 2, "DCM is not 2D");
% Assert square
assert(size(unique(size(dcm)), 1) == 1, "DCM is not a square matrix");
epsilon = 1e-9;
% Assert inverse equivalent to transpose
assert(all(abs(inv(dcm) - dcm') < epsilon, "all"), "DCM inverse is not equivalent to transpose");
% Assert determinant is 1
assert(det(dcm) > 1 - epsilon && det(dcm) < 1 + epsilon, "DCM has determinant not equal to 1");
end

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function c = obstacleCoversObjective(objective, obstacle)
arguments (Input)
objective (1, 1) {mustBeA(objective, 'sensingObjective')};
obstacle (1, 1) {mustBeGeometry}; % this could be expanded to handle n obstacles in 1 call
end
arguments (Output)
c (1, 1) logical;
end
% Check if the obstacle contains the objective's ground position if the
% ground position were raised to the obstacle's center's height
c = obstacle.contains([objective.groundPos, obstacle.center(3)]);
end

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function c = obstacleCrowdsObjective(objective, obstacle, protectedRange)
arguments (Input)
objective (1, 1) {mustBeA(objective, 'sensingObjective')};
obstacle (1, 1) {mustBeGeometry}; % this could be expanded to handle n obstacles in 1 call
protectedRange (1, 1) double;
end
arguments (Output)
c (1, 1) logical;
end
c = norm(obstacle.distance([objective.groundPos, obstacle.center(3)])) <= protectedRange;
end