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How do we specify a polygon (5 sided, 3 sided, 6 sided...) as an obstacle in the costmap RRTplanner.
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I am trying to specify a polygon (pentagon and triangle) as a costmap for the vehicle costmap.
How do I implement that in the costmap. The example use a meshgrid which is usually a square or rectangle obstacle.
Matlab example: Define a set of (x,y) coordinates that correspond to a 3-by-5 meter rectangle.
[x,y] = meshgrid(2:4,2:6);
xyPoints = [x(:),y(:)];
costVal = 0.9;
setCosts(costmap,xyPoints,costVal);
plot(costmap)
title('Costmap with Rectangular Obstacle')
Question: Given a triangle or pentagon vertices, how do we do implement it.
1 Comment
Answers (1)
Cameron Stabile
on 10 Feb 2023
Moved: Remo Pillat
on 8 Mar 2023
Hi Jay,
The best way to go about this currently is using inpolygon. You would first create a rectangular meshgrid of xy coordinates which cover your polygon (defined as 2 N-element vectors corresponding to your polygon vertices, xv and yv), then determine whether they lie in or on the polygon. Those coordinates can then be used in your call to setCosts.
% Define points over full polygonal region
[xx,yy] = meshgrid(linspace(.5,9.5,100),linspace(.5,9.5,100))
xx = 100×100
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
0.5000 0.5909 0.6818 0.7727 0.8636 0.9545 1.0455 1.1364 1.2273 1.3182 1.4091 1.5000 1.5909 1.6818 1.7727 1.8636 1.9545 2.0455 2.1364 2.2273 2.3182 2.4091 2.5000 2.5909 2.6818 2.7727 2.8636 2.9545 3.0455 3.1364
yy = 100×100
0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000
0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909 0.5909
0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818 0.6818
0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727 0.7727
0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636 0.8636
0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545 0.9545
1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455 1.0455
1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364 1.1364
1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273 1.2273
1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182 1.3182
% Define polygon
nSides = 6;
theta = linspace(0,2*pi,nSides);
vertices = 5*[cos(theta(:)) sin(theta(:))] + 5
vertices = 6×2
10.0000 5.0000
6.5451 9.7553
0.9549 7.9389
0.9549 2.0611
6.5451 0.2447
10.0000 5.0000
% Find points within the polygon
in = inpolygon(xx(:),yy(:),vertices(:,1),vertices(:,2))
in = 10000×1 logical array
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0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
% Update the map (replace this with whatever data-structure/method you're using)
map = occupancyMap(Resolution=10);
map.setOccupancy([xx(in) yy(in)],.9);
show(map);
Hope this helps,
Cameron
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