rrt算法路径规划matlab
时间: 2023-08-28 17:06:28 浏览: 43
以下是使用MATLAB实现RRT算法进行路径规划的示例代码:
```matlab
% RRT路径规划算法
% 初始化
clear all;
% 设置起点和终点
start = [0,0];
goal = [10,10];
% 设置障碍物
obstacles = [4,4,1; 5,5,1; 6,6,1; 7,7,1; 8,8,1];
% 设置RRT参数
stepsize = 1;
maxiter = 1000;
goalprob = 0.05;
% 初始化RRT
nodes = [start];
edges = [];
iter = 1;
found = false;
% 开始搜索
while iter <= maxiter && ~found
% 随机采样
if rand() < goalprob
q = goal;
else
q = rand(1,2) * 10;
end
% 找到最近的节点
d = inf;
nearest = [];
for i = 1:size(nodes,1)
dist = norm(nodes(i,:) - q);
if dist < d
d = dist;
nearest = nodes(i,:);
end
end
% 扩展树
newnode = nearest + stepsize*(q - nearest)/d;
if ~collision(newnode, obstacles) % 判断是否有碰撞
nodes = [nodes; newnode];
edges = [edges; nearest, newnode];
if norm(newnode - goal) < 0.5 % 判断是否到达目标点
found = true;
end
end
iter = iter + 1;
end
% 获取路径
if found
path = [goal];
while norm(path(1,:) - start) > 0.5
for i = 1:size(edges,1)
if norm(edges(i,2,:) - path(1,:)) < 0.5
path = [edges(i,1,:); path];
break;
end
end
end
path = [start; path];
else
path = [];
end
% 绘制结果
figure;
hold on;
scatter(start(1), start(2), 'ro', 'LineWidth', 2);
scatter(goal(1), goal(2), 'ro', 'LineWidth', 2);
for i = 1:size(obstacles,1)
circle(obstacles(i,1), obstacles(i,2), obstacles(i,3));
end
for i = 1:size(edges,1)
plot([edges(i,1,1), edges(i,2,1)], [edges(i,1,2), edges(i,2,2)], 'b-', 'LineWidth', 1);
end
if ~isempty(path)
plot(path(:,1), path(:,2), 'r-', 'LineWidth', 2);
end
axis equal;
xlim([-1, 11]);
ylim([-1, 11]);
% 判断是否碰撞
function c = collision(p, obstacles)
c = false;
for i = 1:size(obstacles,1)
if norm(p - obstacles(i,1:2)) < obstacles(i,3)
c = true;
break;
end
end
end
% 绘制圆形障碍物
function circle(x, y, r)
theta = linspace(0, 2*pi);
xunit = r * cos(theta) + x;
yunit = r * sin(theta) + y;
plot(xunit, yunit, 'k-', 'LineWidth', 1);
end
```
该代码使用RRT算法进行路径规划,并考虑了圆形障碍物的碰撞检测。其中,stepsize为RRT扩展树的步长,maxiter为最大迭代次数,goalprob为到达目标点的概率。将该代码保存为.m文件并运行即可看到路径规划结果。