rrt-connect算法matlab代码

当然，我可以为你提供 RRT-Connect 算法的 MATLAB 代码示例。RRT-Connect 是一种基于 Rapidly-exploring Random Trees (RRT) 的路径规划算法，用于在两个给定点之间查找可行路径。以下是一个简单的实现：

% RRT-Connect Algorithm
function path = rrt_connect(start, goal, obstacles, max_iter, step_size)
    % Initialize trees
    tree_start = start;
    tree_goal = goal;
    
    for i = 1:max_iter
        % Randomly sample a point
        if rand() < 0.5
            rand_point = [rand()*100, rand()*100]; % Modify according to your workspace size
        else
            rand_point = goal;
        end
        
        % Extend tree_start towards rand_point
        nearest_start = nearest_neighbor(tree_start, rand_point);
        new_point_start = steer(nearest_start, rand_point, step_size);
        
        if ~collision(new_point_start, nearest_start, obstacles)
            tree_start = add_node(tree_start, nearest_start, new_point_start);
            
            % Connect tree_goal towards new_point_start
            nearest_goal = nearest_neighbor(tree_goal, new_point_start);
            new_point_goal = steer(nearest_goal, new_point_start, step_size);
            
            if ~collision(new_point_goal, nearest_goal, obstacles)
                tree_goal = add_node(tree_goal, nearest_goal, new_point_goal);
                
                % Check if the trees have met
                if norm(new_point_start - new_point_goal) <= step_size
                    path = generate_path(tree_start, tree_goal);
                    return;
                end
            end
        end
        
        % Swap trees if necessary
        if rand() < 0.5
            temp = tree_start;
            tree_start = tree_goal;
            tree_goal = temp;
        end
    end
    
    % No path found
    error('No feasible path found');
end

% Helper functions
function nearest_node = nearest_neighbor(tree, point)
    distances = vecnorm(tree - point, 2, 2);
    [~, index] = min(distances);
    nearest_node = tree(index, :);
end

function new_point = steer(from, to, step_size)
    direction = (to - from) / norm(to - from);
    new_point = from + direction * step_size;
end

function is_collision = collision(point, from, obstacles)
    for i = 1:size(obstacles, 1)
        if norm(point - from) <= norm(obstacles(i, :) - from)
            is_collision = true;
            return;
        end
    end
    
    is_collision = false;
end

function new_tree = add_node(tree, from, to)
    new_tree = [tree; to];
end

function path = generate_path(tree_start, tree_goal)
    path_start = trace_path(tree_start);
    path_goal = flip(trace_path(tree_goal));
    path = [path_start; path_goal];
end

function path = trace_path(tree)
    path = tree(end, :);
    
    while ~isempty(path) && ~isequal(path(1, :), tree(1, :))
        parent_index = find(ismember(tree, path(1, :), 'rows'));
        path = [tree(parent_index, :); path];
    end
end

请注意，这只是一个简单的示例代码，你需要根据你的具体场景进行修改和适配。你需要提供起点、终点、障碍物、最大迭代次数和步长等参数来调用 `rrt_connect` 函数。如果找到可行路径，它将返回一系列点构成的路径。如果没有找到可行路径，它将抛出错误。

希望这可以帮助到你！如果你有任何其他问题，请随时问我。