【二维路径规划】基于人工势场求解机器人路径规划问题附matlab代码

1 简介

移动机器人的路径规划是移动机器人研究领域中的一个热点问题。

​2 部分代码

%% 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 routestart = [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);​

3 仿真结果

4 参考文献

[1]李欣, 朱大奇. 基于人工势场法的自治水下机器人路径规划[J]. 上海海事大学学报, 2010, 31(2):5.

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部分理论引用网络文献，若有侵权联系博主删除。