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a implement of Artificial Potential Field in matlab
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% | |
% PotentialFieldScript.m | |
% | |
%% Generate some points | |
nrows = 400; | |
ncols = 600; | |
obstacle = false(nrows, ncols); | |
[x, y] = meshgrid (1:ncols, 1:nrows); | |
%% Generate some obstacle | |
obstacle (300:end, 100:250) = true; | |
obstacle (150:200, 400:500) = true; | |
t = ((x - 200).^2 + (y - 50).^2) < 50^2; | |
obstacle(t) = true; | |
t = ((x - 400).^2 + (y - 300).^2) < 100^2; | |
obstacle(t) = true; | |
%% Compute distance transform | |
d = bwdist(obstacle); | |
% Rescale and transform distances | |
d2 = (d/100) + 1; | |
d0 = 2; | |
nu = 800; | |
repulsive = nu*((1./d2 - 1/d0).^2); | |
repulsive (d2 > d0) = 0; | |
%% Display repulsive potential | |
figure; | |
m = mesh (repulsive); | |
m.FaceLighting = 'phong'; | |
axis equal; | |
title ('Repulsive Potential'); | |
%% Compute attractive force | |
goal = [400, 50]; | |
xi = 1/700; | |
attractive = xi * ( (x - goal(1)).^2 + (y - goal(2)).^2 ); | |
figure; | |
m = mesh (attractive); | |
m.FaceLighting = 'phong'; | |
axis equal; | |
title ('Attractive Potential'); | |
%% Display 2D configuration space | |
figure; | |
imshow(~obstacle); | |
hold on; | |
plot (goal(1), goal(2), 'r.', 'MarkerSize', 25); | |
hold off; | |
axis ([0 ncols 0 nrows]); | |
axis xy; | |
axis on; | |
xlabel ('x'); | |
ylabel ('y'); | |
title ('Configuration Space'); | |
%% Combine terms | |
f = attractive + repulsive; | |
figure; | |
m = mesh (f); | |
m.FaceLighting = 'phong'; | |
axis equal; | |
title ('Total Potential'); | |
%% Plan route | |
start = [50, 350]; | |
route = GradientBasedPlanner (f, start, goal, 1000); | |
%% Plot the energy surface | |
figure; | |
m = mesh (f); | |
axis equal; | |
%% Plot ball sliding down hill | |
[sx, sy, sz] = sphere(20); | |
scale = 20; | |
sx = scale*sx; | |
sy = scale*sy; | |
sz = scale*(sz+1); | |
hold on; | |
p = mesh(sx, sy, sz); | |
p.FaceColor = 'red'; | |
p.EdgeColor = 'none'; | |
p.FaceLighting = 'phong'; | |
hold off; | |
for i = 1:size(route,1) | |
P = round(route(i,:)); | |
z = f(P(2), P(1)); | |
p.XData = sx + P(1); | |
p.YData = sy + P(2); | |
p.ZData = sz + f(P(2), P(1)); | |
drawnow; | |
drawnow; | |
end | |
%% quiver plot | |
[gx, gy] = gradient (-f); | |
skip = 20; | |
figure; | |
xidx = 1:skip:ncols; | |
yidx = 1:skip:nrows; | |
quiver (x(yidx,xidx), y(yidx,xidx), gx(yidx,xidx), gy(yidx,xidx), 0.4); | |
axis ([1 ncols 1 nrows]); | |
hold on; | |
ps = plot(start(1), start(2), 'r.', 'MarkerSize', 30); | |
pg = plot(goal(1), goal(2), 'g.', 'MarkerSize', 30); | |
p3 = plot (route(:,1), route(:,2), 'r', 'LineWidth', 2); |
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can you share function GradientBasedPlanner() please?