How do we specify a polygon (5 sided, 3 sided, 6 sided...) as an obstacle in the costmap RRTplanner.

1 次查看（过去 30 天）
Bay Jay
Bay Jay 2023-2-6
移动：Remo Pillat 2023-3-8
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.

请先登录，再回答此问题。

回答（1 个）

Cameron Stabile
Cameron Stabile 2023-2-10
移动：Remo Pillat 2023-3-8
Ran in:
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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 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0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 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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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 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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 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 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 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 1 1 1 1 1 1 1 1 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 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 1 1 1 1 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 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 1 1 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 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 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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