-
Notifications
You must be signed in to change notification settings - Fork 0
/
GridWorld.m
501 lines (441 loc) · 20.1 KB
/
GridWorld.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
classdef GridWorld < matlab.System
% GridWorld represents a 12x12 deterministic grid world with 3 robots.
% Copyright 2020-2022 The MathWorks, Inc.
% Public, tunable properties
properties
% Initial position of robots
InitialStates (3,2) double = [2 2; 11 4; 3 12]
end
% Public, non-tunable properties
properties(Nontunable)
% Obstacle matrix
Obstacles double = -1
% Max step count
MaxStepCount (1,1) double = 500
end
properties(DiscreteState)
% Discretized XY space with cells containing 0.5 or 1.0
% 0: unexplored
% 0.25: explored by robot A
% 0.50: explored by robot B
% 0.75: explored by robot B
% 1.0: obstacle
Grid
% States of robot A,B: [rowA colA; rowB colB]
States
% Step count
StepCount
% Individual cell exploration count
NumExploredCells
end
% Pre-computed constants
properties(Access = private)
% Handle to figure
Figure
% Grid size [numrows numcols]
Size (1,2) double = [12 12]
end
methods
% Constructor
function this = GridWorld(varargin)
% Support name-value pair arguments when constructing object
setProperties(this,nargin,varargin{:})
end
end
methods(Access = protected)
%% Common functions
function setupImpl(obj) %#ok<MANU>
% Perform one-time calculations, such as computing constants
end
function [observations,rewards,isdone] = stepImpl(obj,actions)
% Implement algorithm. Calculate y as a function of input u and
% discrete states.
numRobots = 3;
% Rewards are:
% Agent moves to unexplored cell: +20
% Agent moves to explored cell: 0
% Agent tries to move out of grid: -10
% Agent collides with another agent: -10
% Agent collides with obstacle: -10
% Movement penalty: -1
% Lazy penalty: -2
% On full coverage: +4000 * coverage contribution
% move robots to their next state
%next_states = zeros(numRobots,2);
rewards = zeros(numRobots,1);
isdone = 0;
next_states = obj.States;
for idx = 1:numRobots
state = obj.States(idx,:);
action = actions(idx);
switch(action)
% case 0
% % Wait
% next_states(idx,:) = state;
% rewards(idx) = rewards(idx) - 10; % lazy penalty
case 1
% Move up
if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [1 0];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go up
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 2
% Move down
if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [-1 0];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go down
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 3
% Move left
if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [0 -1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go left
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 4
% Move right
if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [0 1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go right
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 5
% Move right-up NorthEast
if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [1 1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go right-up NorthEast
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 6
% Move Left up NorthWest
if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [1 -1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go Left up NorthWest
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 7
% Move Right Down South East
if state(1) > 1 && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [-1 1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go Right Down South East
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
case 8
% Move Left Down South West
if state(1) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:))
next_states(idx,:) = state + [-1 -1];
rewards(idx) = rewards(idx) - 1;
else
% add a negative reward for trying to go Left Down South West
next_states(idx,:) = state;
rewards(idx) = rewards(idx) - 10;
end
end
end
% update grid and reward agents for new exploration
for idx = 1:numRobots
r = next_states(idx,1);
c = next_states(idx,2);
if obj.Grid(r,c) == 0.0
% robot explores an unexplored cell
rewards(idx) = rewards(idx) + 20;
% update grid values
switch(idx)
case 1
obj.Grid(r,c) = 0.25; % explored by A
obj.NumExploredCells = obj.NumExploredCells + [1 0 0];
case 2
obj.Grid(r,c) = 0.5; % explored by B
obj.NumExploredCells = obj.NumExploredCells + [0 1 0];
case 3
obj.Grid(r,c) = 0.75; % explored by C
obj.NumExploredCells = obj.NumExploredCells + [0 0 1];
end
end
end
% coverage metrics
totalExploredCells = sum(obj.NumExploredCells);
totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all');
if totalExploredCells >= totalCells
isdone = 1;
rewards = rewards + 4000 * (totalExploredCells'/totalCells);
end
% Observation for each agent is a 12x12 4-channel image. The
% channels are:
% 1. Obstacle channel - cells with obstacles are 1, rest 0
% 2. Self channel - cell with the agent's state is 1, rest 0
% 3. Friend channel - cell with other agent's state is 1, rest 0
% 4. Coverage channel - cells that are unexplored are 1, rest 0
observations = zeros(obj.Size(1),obj.Size(2),4,numRobots);
for idx = 1:numRobots
obstacleChannel = 1.0 * (obj.Grid == 1.0);
selfIdx = idx;
selfRow = next_states(selfIdx,1);
selfCol = next_states(selfIdx,2);
selfChannel = zeros(obj.Size);
selfChannel(selfRow,selfCol) = 1.0;
friendIdxs = idx ~= (1:numRobots);
friendRows = next_states(friendIdxs,1);
friendCols = next_states(friendIdxs,2);
friendChannel = zeros(obj.Size);
friendChannel(friendRows(1),friendCols(1)) = 1.0;
friendChannel(friendRows(2),friendCols(2)) = 1.0;
coverageChannel = 1.0 * (obj.Grid == 0);
observations(:,:,1,idx) = obstacleChannel;
observations(:,:,2,idx) = selfChannel;
observations(:,:,3,idx) = friendChannel;
observations(:,:,4,idx) = coverageChannel;
end
% Scale down rewards
rewards = rewards./20;
% DEBUG
if all(next_states(1,:)==next_states(2,:)) || ...
all(next_states(2,:)==next_states(3,:)) || ...
all(next_states(1,:)==next_states(3,:))
fprintf('Assertion: Invalid state.\n');
end
% Update states
obj.States = next_states;
obj.StepCount = obj.StepCount + 1;
% plot the environment
if obj.StepCount <= obj.MaxStepCount
plot(obj);
end
end
function resetImpl(obj)
% Initialize / reset discrete-state properties
% set unexplored cells
obj.Grid = zeros(obj.Size);
% set obstacle cells
if ~isequal(obj.Obstacles,-1)
for idx = 1:size(obj.Obstacles,1)
r = obj.Obstacles(idx,1);
c = obj.Obstacles(idx,2);
obj.Grid(r,c) = 1.0;
end
end
% set step count
obj.StepCount = 0;
% explored cells
obj.NumExploredCells = ones(1,3);
% set robot cells
sA = obj.InitialStates(1,:);
sB = obj.InitialStates(2,:);
sC = obj.InitialStates(3,:);
obj.Grid(sA(1),sA(2)) = 0.25;
obj.Grid(sB(1),sB(2)) = 0.50;
obj.Grid(sC(1),sC(2)) = 0.75;
obj.States = obj.InitialStates;
end
%% Backup/restore functions
function s = saveObjectImpl(obj)
% Set properties in structure s to values in object obj
% Set public properties and states
s = [email protected](obj);
% Set private and protected properties
%s.myproperty = obj.myproperty;
end
function loadObjectImpl(obj,s,wasLocked)
% Set properties in object obj to values in structure s
% Set private and protected properties
% obj.myproperty = s.myproperty;
% Set public properties and states
[email protected](obj,s,wasLocked);
end
%% Simulink functions
function ds = getDiscreteStateImpl(obj)
% Return structure of properties with DiscreteState attribute
ds.Grid = obj.Grid;
ds.States = obj.States;
ds.StepCount = obj.StepCount;
ds.NumExploredCells = obj.NumExploredCells;
end
function flag = isInputSizeMutableImpl(obj,index) %#ok<INUSD>
% Return false if input size cannot change
% between calls to the System object
flag = false;
end
function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok<MANU>
% Return size for each output port
out1 = [12 12 4 3]; % observation
out2 = [3 1]; % reward
out3 = [1 1]; % isdone
end
function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok<MANU>
% Return data type for each output port
out1 = "double";
out2 = "double";
out3 = "double";
end
function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok<MANU>
% Return true for each output port with complex data
out1 = false;
out2 = false;
out3 = false;
end
function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok<MANU>
% Return true for each output port with fixed size
out1 = true;
out2 = true;
out3 = true;
end
function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name)
% Return size, data type, and complexity of discrete-state
% specified in name
if strcmpi(name,'Grid')
sz = obj.Size;
dt = "double";
cp = false;
elseif strcmpi(name,'States')
sz = [3 2];
dt = "double";
cp = false;
elseif strcmpi(name,'StepCount')
sz = [1 1];
dt = "double";
cp = false;
elseif strcmpi(name,'NumExploredCells')
sz = [1 3];
dt = "double";
cp = false;
else
error(['Error: Incorrect State Name: ', name.']);
end
end
function icon = getIconImpl(obj) %#ok<MANU>
% Define icon for System block
icon = mfilename("class"); % Use class name
end
end
methods(Static, Access = protected)
%% Simulink customization functions
function header = getHeaderImpl
% Define header panel for System block dialog
header = matlab.system.display.Header(mfilename("class"));
end
function group = getPropertyGroupsImpl
% Define property section(s) for System block dialog
group = matlab.system.display.Section(mfilename("class"));
end
end
methods(Access=private)
function collision = checkCollision(obj,new_state,other_states)
% Create array of occupied states
if isequal(obj.Obstacles,-1)
occupiedStates = other_states;
else
occupiedStates = [other_states; obj.Obstacles];
end
% check collision
collision = any(all(new_state==occupiedStates,2));
end
function plot(obj)
persistent ax cells robots
if isempty(ax) || ~isvalid(ax)
% build figure
f = figure;
f.Position = [195 120 400 300];
%f.Visible = 'on'; % force external figure
ax = gca(f);
hold(ax,'on');
if ~isequal(obj.Obstacles,-1)
cmap = [255 255 255; ... % white (unexplored)
255 140 105; ... % light red (explored by A)
152 251 152; ... % light green (explored by B)
176 226 255; ... % light blue (explored by C)
0 0 0]./255; % black (obstacles)
else
cmap = [255 255 255;... % white (unexplored)
255 140 105; ... % light red (explored by A)
152 251 152; ... % light green (explored by B)
176 226 255; ... % light blue (explored by C)
]./255; % black (obstacles)
end
colormap(ax,cmap);
% plot cells
cdata = obj.Grid;
cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata);
% plot grid lines
x = 0:1:obj.Size(2);
y = 0:1:obj.Size(1);
[X,Y] = meshgrid(x,y);
plot(ax,X,Y,'Color',[0.94 0.94 0.94]);
plot(ax,Y,X,'Color',[0.94 0.94 0.94]);
% plot robots
sA = obj.InitialStates(1,:);
sB = obj.InitialStates(2,:);
sC = obj.InitialStates(3,:);
robots = gobjects(1,2);
robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1);
robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1);
robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1);
% time text
totalExploredCells = sum(obj.NumExploredCells);
totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all');
coverage = totalExploredCells / totalCells * 100;
title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage));
ax.XTick = 0:1:obj.Size(1);
ax.YTick = 0:1:obj.Size(2);
ax.XTickLabel = {};
ax.YTickLabel = {};
axis(ax,'equal');
ax.XLim = [0 obj.Size(1)];
ax.YLim = [0 obj.Size(2)];
ax.Box = 'on';
end
% update color map
cmap = [255 255 255; ... % white (unexplored)
255 140 105; ... % light red (explored by A)
152 251 152; ... % light green (explored by B)
176 226 255; ... % light blue (explored by C)
0 0 0]./255; % black (obstacles)
if all(obj.Grid~=0,'all')
cmap = cmap(2:end,:); % no unexplored cells
end
if isequal(obj.Obstacles,-1)
cmap = cmap(1:end-1,:); % no obstacles
end
colormap(ax,cmap);
% update cell colors
cdata = obj.Grid;
cells.CData = cdata;
% update robot positions
for idx = 1:3
s = obj.States(idx,:);
robots(idx).Position = [s(2)-1 s(1)-1 1 1];
end
% update info text
totalExploredCells = sum(obj.NumExploredCells);
totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all');
coverage = totalExploredCells / totalCells * 100;
ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage);
ax.XLim = [0 obj.Size(1)];
ax.YLim = [0 obj.Size(2)];
grid(ax,'on');
drawnow();
end
end
end