基于D*与动态窗口法的动态路径规划 matlab代码

以下是一个基于D*与动态窗口法的动态路径规划的matlab代码示例：

% D*算法路径规划
function [path, cost] = Dstar(start, goal, map)
% 初始化
U = []; 
k = 0; 
R = Inf(size(map)); 
R(goal(1), goal(2)) = 0;
U = [U; goal, 0]; 
% 启发式函数
heuristic = @(pos) norm(pos - goal);
% 移动代价
move_cost = @(pos) map(pos(1), pos(2));
% 动态窗口法
while true
    if isempty(U)
        path = []; 
        cost = Inf; 
        return;
    end
    % 获取U中距离起点最近的点
    [~, idx] = min(U(:,3)); 
    curr = U(idx, :); 
    if all(curr(1:2) == start)
        break; 
    end
    U(idx, :) = []; 
    k = k + 1; 
    R(curr(1), curr(2)) = curr(3); 
    % 获取当前点的邻居节点
    neighbors = get_neighbors(curr, map); 
    for i = 1:size(neighbors, 1)
        pos = neighbors(i, :); 
        if R(pos(1), pos(2)) > R(curr(1), curr(2)) + move_cost(pos) + heuristic(pos) - heuristic(curr(1:2))
            R(pos(1), pos(2)) = R(curr(1), curr(2)) + move_cost(pos) + heuristic(pos) - heuristic(curr(1:2));
            U = [U; pos, R(pos(1), pos(2)) + heuristic(pos)]; 
        end
    end
end
% 生成路径
path = [start; backtrack(start, goal, map, R, heuristic)];
cost = R(start(1), start(2)); 
end

% 获取当前点的邻居节点
function neighbors = get_neighbors(pos, map)
[row, col] = size(map);
neighbors = [];
if pos(1) > 1
    if map(pos(1) - 1, pos(2)) ~= Inf
        neighbors = [neighbors; pos(1) - 1, pos(2)];
    end
end
if pos(1) < row
    if map(pos(1) + 1, pos(2)) ~= Inf
        neighbors = [neighbors; pos(1) + 1, pos(2)];
    end
end
if pos(2) > 1
    if map(pos(1), pos(2) - 1) ~= Inf
        neighbors = [neighbors; pos(1), pos(2) - 1];
    end
end
if pos(2) < col
    if map(pos(1), pos(2) + 1) ~= Inf
        neighbors = [neighbors; pos(1), pos(2) + 1];
    end
end
end

% 回溯函数
function path = backtrack(start, goal, map, R, heuristic)
path = [goal];
while any(path(1,:) ~= start)
    neighbors = get_neighbors(path(1,:), map); 
    costs = [];
    for i = 1:size(neighbors, 1)
        pos = neighbors(i,:);
        cost = R(pos(1), pos(2)) + norm(pos - path(1,:)) + heuristic(start) - heuristic(pos);
        costs = [costs; cost];
    end
    [~, idx] = min(costs); 
    path = [neighbors(idx,:); path];
end
end

% 动态路径规划
function [path, cost] = dynamic_path_planning(start, goal, map)
% 初始化
path = [start];
cost = 0;
while true
    % 重新规划路径
    [new_path, new_cost] = Dstar(path(end,:), goal, map);
    % 判断是否无法到达终点
    if isempty(new_path) && new_cost == Inf
        break;
    end
    % 判断是否到达终点
    if all(new_path(end,:) == goal)
        path = [path; new_path(2:end,:)];
        cost = cost + new_cost;
        break;
    end
    % 动态调整路径
    for i = 2:size(new_path, 1) - 1
        if ~is_collision(new_path(i,:), map)
            path = [path; new_path(i,:)];
            cost = cost + move_cost(path(end-1,:), path(end,:));
        else
            break;
        end
    end
end
end

% 判断是否与障碍物发生碰撞
function is_collision = is_collision(pos, map)
is_collision = map(pos(1), pos(2)) == Inf;
end

% 移动代价
function cost = move_cost(pos1, pos2)
cost = norm(pos1 - pos2);
end

在使用该代码时，需要传入起点、终点和地图，地图中1表示可通行区域，Inf表示障碍物。其中，Dstar函数实现D*算法路径规划，get_neighbors函数获取当前点的邻居节点，backtrack函数用于回溯生成路径，dynamic_path_planning函数实现动态路径规划，is_collision函数用于判断是否与障碍物发生碰撞，move_cost函数计算移动代价。