-
Notifications
You must be signed in to change notification settings - Fork 17
/
Copy pathBug2.m
267 lines (231 loc) · 9.69 KB
/
Bug2.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
%BUG2 Bug navigation class
%
% The class implements the bug2 navigation algorithm. This is a simple
% automaton that performs reactive navigation, that is, it can only sense
% the immediate presence of an obstacle.
%
% Methods::
% Bug2 Constructor
% run Find a path from start to goal
% plot Display the obstacle map
% display Display state/parameters in human readable form
% char Convert to string
%
% Example::
% load map1 % load the map
% bug = Bug2(map); % create navigation object
% start = [20,10];
% goal = [50,35];
% bug.run(start, goal); % animate path
%
% Reference::
% - Dynamic path planning for a mobile automaton with limited information on the environment,,
% V. Lumelsky and A. Stepanov,
% IEEE Transactions on Automatic Control, vol. 31, pp. 1058-1063, Nov. 1986.
% - Robotics, Vision & Control, Sec 5.1.2,
% Peter Corke, Springer, 2011.
%
% See also Navigation, DXform, Dstar, PRM.
% Copyright 2022-2023 Peter Corke, Witold Jachimczyk, Remo Pillat
classdef Bug2 < Navigation
properties(Access=protected)
H % hit points
j % number of hit points
mline % line from starting position to goal
step % state, in step 1 or step 2 of algorithm
edge % edge list
k % edge index
end
methods
function bug = Bug2(varargin)
%Bug2.Bug2 Construct a Bug2 navigation object
%
% B = Bug2(MAP, OPTIONS) is a bug2 navigation object, and MAP is an occupancy grid,
% a representation of a planar world as a matrix whose elements are 0 (free
% space) or 1 (occupied).
%
% Options::
% 'goal',G Specify the goal point (1x2)
% 'inflate',K Inflate all obstacles by K cells.
%
% See also Navigation.Navigation.
% invoke the superclass constructor
bug = bug@Navigation(varargin{:});
bug.H = [];
bug.j = 1;
bug.step = 1;
end
function pp = run(bug, start, goal, varargin)
%Bug2.run Find a path using Bug2 reactive navigation algorithm
%
% B.run(START, GOAL, OPTIONS) is the path (Nx2) from START (1x2) to GOAL
% (1x2). Row are the coordinates of successive points along the path. If
% either START or GOAL is [] the grid map is displayed and the user is
% prompted to select a point by clicking on the plot.
%
% Options::
% 'animate' show a simulation of the robot moving along the path
% 'movie',M create a movie
% 'current' show the current position position as a black circle
%
% Notes::
% - START and GOAL are given as X,Y coordinates in the grid map, not as
% MATLAB row and column coordinates.
% - START and GOAL are tested to ensure they lie in free space.
% - The Bug2 algorithm is completely reactive so there is no planning
% method.
% - If the bug does a lot of back tracking, it's hard to see the current
% position, use the 'current' option.
% - For the movie option if M contains an extension a movie file with that
% extension is created. Otherwise a folder will be created containing
% individual frames.
%
% See also Animate.
opt.animate = false;
opt.movie = [];
opt.current = false;
opt = tb_optparse(opt, varargin);
if ~isempty(opt.movie)
anim = Animate(opt.movie);
opt.animate = true;
end
% make sure start and goal are set and valid
bug.start = []; bug.goal = [];
bug.checkquery(start, goal);
% compute the m-line
% create homogeneous representation of the line
% line*[x y 1]' = 0
bug.mline = homline(bug.start(1), bug.start(2), ...
bug.goal(1), bug.goal(2));
bug.mline = bug.mline / norm(bug.mline(1:2));
if opt.animate
bug.plot();
bug.plot_mline();
end
% iterate using the next() method until we reach the goal
robot = bug.start(:);
bug.step = 1;
path = bug.start(:);
while true
if opt.animate
plot(robot(1), robot(2), 'g.', 'MarkerSize', 12);
if opt.current
h = plot(robot(1), robot(2), 'ko', 'MarkerSize', 8);
end
drawnow
if ~isempty(opt.movie)
anim.add();
end
if opt.current
delete(h)
end
end
% move to next point on path
robot = bug.next(robot);
% are we there yet?
if isempty(robot)
% yes, exit the loop
break
else
% no, append it to the path
path = [path robot(:)]; %#ok<AGROW>
end
end
if ~isempty(opt.movie)
anim.close();
end
% only return the path if required
if nargout > 0
pp = path';
end
end
function plot_mline(bug, ls)
% parameters of the M-line, direct from initial position to goal
% as a vector mline, such that [robot 1]*mline = 0
if nargin < 2
ls = 'k--';
end
dims = axis;
xmin = dims(1); xmax = dims(2);
ymin = dims(3); ymax = dims(4);
hold on
if bug.mline(2) == 0
% handle the case that the line is vertical
plot([start(1) start(1)], [ymin ymax], 'k--');
else
x = [xmin xmax]';
y = -[x [1;1]] * [bug.mline(1); bug.mline(3)] / bug.mline(2);
plot(x, y, ls);
end
end
function n = next(bug, robot)
% implement the main state machine for bug2
n = [];
robot = robot(:);
% these are coordinates (x,y)
if bug.step == 1
% Step 1. Move along the M-line toward the goal
if vecnorm(bug.goal - robot) == 0 % are we there yet?
return
end
% motion on line toward goal
d = bug.goal-robot;
if abs(d(1)) > abs(d(2))
% line slope less than 45 deg
dx = sign(d(1));
L = bug.mline;
y = -( (robot(1)+dx)*L(1) + L(3) ) / L(2);
dy = round(y - robot(2));
else
% line slope greater than 45 deg
dy = sign(d(2));
L = bug.mline;
x = -( (robot(2)+dy)*L(2) + L(3) ) / L(1);
dx = round(x - robot(1));
end
% detect if next step is an obstacle
if bug.isoccupied(robot + [dx; dy])
bug.message('(%d,%d) obstacle!', n);
bug.H(bug.j,:) = robot; % define hit point
bug.step = 2;
% get a list of all the points around the obstacle
bug.edge = edgelist(bug.occgridnav == 0, robot);
bug.k = 2; % skip the first edge point, we are already there
else
n = robot + [dx; dy];
end
end % step 1
if bug.step == 2
% Step 2. Move around the obstacle until we reach a point
% on the M-line closer than when we started.
if vecnorm(bug.goal-robot) == 0 % are we there yet?
return
end
if bug.k <= size(bug.edge,2)
n = bug.edge(:,bug.k); % next edge point
else
% we are at the end of the list of edge points, we
% are back where we started. Step 2.c test.
error('RTB:bug2:noplan', 'robot is trapped')
end
% are we on the M-line now ?
if abs( [robot' 1]*bug.mline') <= 0.5
bug.message('(%d,%d) moving along the M-line', n);
% are closer than when we encountered the obstacle?
if vecnorm(robot-bug.goal) < vecnorm(bug.H(bug.j,:)'-bug.goal)
% back to moving along the M-line
bug.j = bug.j + 1;
bug.step = 1;
return;
end
end
% no, keep going around
bug.message('(%d,%d) keep moving around obstacle', n)
bug.k = bug.k+1;
end % step 2
end % next
function plan(~)
error('RTB:Bug2:badcall', 'This class has no plan method');
end
end % methods
end % classdef