RRT算法 规划返回路径 matlab代码

以下是一个简单的RRT算法规划返回路径的matlab代码：

% 定义起点和终点
start_point = [0, 0];
goal_point = [10, 10];

% 定义障碍物
obstacle = [3, 3; 4, 3; 4, 4; 3, 4];

% 定义RRT算法参数
max_iter = 1000;
max_distance = 0.5;
goal_tolerance = 0.5;

% 初始化树
tree(1).point = start_point;
tree(1).parent = 0;

% 开始RRT算法
for i = 2:max_iter
    % 生成随机点
    if rand() < goal_tolerance
        random_point = goal_point;
    else
        random_point = [rand()*10, rand()*10];
    end
    
    % 寻找最近的点
    min_distance = Inf;
    for j = 1:length(tree)
        distance = norm(random_point - tree(j).point);
        if distance < min_distance
            min_distance = distance;
            nearest_point = tree(j).point;
            nearest_index = j;
        end
    end
    
    % 生成新的点
    if min_distance > max_distance
        new_point = nearest_point + max_distance*(random_point - nearest_point)/min_distance;
    else
        new_point = random_point;
    end
    
    % 检查新的点是否在障碍物中
    if inpolygon(new_point(1), new_point(2), obstacle(:,1), obstacle(:,2))
        continue;
    end
    
    % 添加新的点到树中
    tree(end+1).point = new_point;
    tree(end).parent = nearest_index;
    
    % 检查是否到达终点
    if norm(new_point - goal_point) < goal_tolerance
        break;
    end
end

% 生成返回路径
path = [tree(end).point];
while tree(end).parent ~= 0
    tree(end) = tree(tree(end).parent);
    path = [tree(end).point; path];
end

% 绘制树和路径
figure;
hold on;
% 绘制障碍物
patch(obstacle(:,1), obstacle(:,2), 'k');
% 绘制树
for i = 1:length(tree)
    if tree(i).parent ~= 0
        plot([tree(i).point(1), tree(tree(i).parent).point(1)], [tree(i).point(2), tree(tree(i).parent).point(2)], 'b');
    end
end
% 绘制路径
plot(path(:,1), path(:,2), 'r', 'LineWidth', 2);
plot(start_point(1), start_point(2), 'go', 'MarkerSize', 10);
plot(goal_point(1), goal_point(2), 'ro', 'MarkerSize', 10);
axis equal;

该代码将生成一个随机树，并在障碍物中寻找一条路径以连接起点和终点。该代码还包括一个简单的路径规划算法，用于返回最短路径。