0 专栏介绍

🔥附C++/Python/Matlab全套代码🔥课程设计、毕业设计、创新竞赛必备！详细介绍全局规划(图搜索、采样法、智能算法等)；局部规划(DWA、APF等)；曲线优化(贝塞尔曲线、B样条曲线等)。

🚀详情：图解自动驾驶中的运动规划(Motion Planning)，附几十种规划算法

1 Theta*算法局限性

Theta*的运行瓶颈在于，每次扩展节点 $v$ 的邻节点 $w$ 时，都需要对 $\mathrm{parent}(v)$ 和 $w$ 进行一次Bresenham视线检测。然而，大部分邻节点最终不会被扩展，大量应用在视线检测上的计算资源被浪费。

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Theta*的变种算法Lazy Theta*算法通过延迟评估技术提升Theta*的路径搜索速度。实验证明，在26邻域三维地图上，Lazy Theta*的视线检查数量比Theta*减少了一个数量级，且路径长度没有增加。

2 Lazy Theta*算法原理

Lazy Theta*在扩展节点 $v$ 的邻节点 $w$ 时，默认 $\mathrm{parent}(v)$ 和 $w$ 间存在视线，而无需对 $\mathrm{parent}(v)$ 和 $w$ 进行碰撞检测。当以节点 $w$ 为基础开始扩展时，才正式对它与父节点 $\mathrm{parent}(v)$ 计算视线。若视线存在，则无需更新信息(path2)；若视线不存在，则在邻域重新选择父节点(path1)。

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Lazy Theta*的算法流程如下所示。

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3 Theta* VS. Lazy Theta*

Lazy Theta*牺牲了一定的路径优度，因为节点 $v$ 与其父节点间可能存在障碍，使节点 $v$ 的 $g$ 值往往小于真实值，导致从Open表中取出的优先节点可能并非最优的，所以Lazy Theta*的规划路径可能会更长。同时，当判定节点与其父节点间存在障碍后， $v$ 的父节点只能从邻域中更新，可能产生锯齿。Theta*与Lazy Theta*的对比实例如下

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4 仿真实现

4.1 ROS C++实现

核心代码如下

bool LazyThetaStar::plan(const unsigned char* global_costmap, const Node& start, const Node& goal,std::vector<Node>& path, std::vector<Node>& expand)
{// initializecosts_ = global_costmap;closed_list_.clear();path.clear();expand.clear();motion_ = getMotion();// push the start node into open liststd::priority_queue<Node, std::vector<Node>, compare_cost> open_list;open_list.push(start);// main processwhile (!open_list.empty()){// pop current node from open listNode current = open_list.top();open_list.pop();_setVertex(current);if (current.g_ >= INFINITE_COST)continue;// current node does not exist in closed listif (closed_list_.find(current) != closed_list_.end())continue;closed_list_.insert(current);expand.push_back(current);// goal foundif (current == goal){path = _convertClosedListToPath(closed_list_, start, goal);return true;}// explore neighbor of current nodefor (const auto& m : motion_){// explore a new node// path 1Node node_new = current + m;  // add the x_, y_, g_node_new.h_ = dist(node_new, goal);node_new.id_ = grid2Index(node_new.x_, node_new.y_);node_new.pid_ = current.id_;// current node do not exist in closed listif (closed_list_.find(node_new) != closed_list_.end())continue;// next node hit the boundary or obstacleif ((node_new.id_ < 0) || (node_new.id_ >= ns_) || (costs_[node_new.id_] >= lethal_cost_ * factor_))continue;// get parent nodeNode parent;parent.id_ = current.pid_;index2Grid(parent.id_, parent.x_, parent.y_);auto find_parent = closed_list_.find(parent);if (find_parent != closed_list_.end()){parent = *find_parent;// path 2_updateVertex(parent, node_new);}open_list.push(node_new);}}return false;
}

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4.2 Python实现

核心代码如下

def plan(self):# OPEN set with priority and CLOSED setOPEN = []heapq.heappush(OPEN, self.start)CLOSED = []while OPEN:node = heapq.heappop(OPEN)# set vertex: path 1try:...except:pass# exists in CLOSED setif node in CLOSED:continue# goal foundif node == self.goal:CLOSED.append(node)return self.extractPath(CLOSED), CLOSEDfor node_n in self.getNeighbor(node):                # exists in CLOSED setif node_n in CLOSED:continue# path1node_n.parent = node.currentnode_n.h = self.h(node_n, self.goal)try:p_index = CLOSED.index(Node(node.parent))node_p = CLOSED[p_index]except:node_p = Noneif node_p:# path2self.updateVertex(node_p, node_n)# goal foundif node_n == self.goal:heapq.heappush(OPEN, node_n)break# update OPEN setheapq.heappush(OPEN, node_n)CLOSED.append(node)return ([], []), []

4.3 Matlab实现

核心代码如下

while ~isempty(OPEN)% popf = OPEN(:, 3) + OPEN(:, 4);[~, index] = min(f);cur_node = OPEN(index, :);OPEN(index, :) = [];% set vertex: path 1p_index = loc_list(cur_node(5: 6), CLOSED, [1, 2]);...% exists in CLOSED setif loc_list(cur_node, CLOSED, [1, 2])continueend% update expand zoneif ~loc_list(cur_node, EXPAND, [1, 2])EXPAND = [EXPAND; cur_node(1:2)];end% goal foundif cur_node(1) == goal(1) && cur_node(2) == goal(2)CLOSED = [cur_node; CLOSED];goal_reached = true;cost = cur_node(3);breakendif (cur_node(1) ==17) &&(cur_node(2) == 26)cur_node(1);end% explore neighborsfor i = 1:motion_num% path 1node_n = [cur_node(1) + motion(i, 1), ...cur_node(2) + motion(i, 2), ...cur_node(3) + motion(i, 3), ...0, ...cur_node(1), cur_node(2)];node_n(4) = h(node_n(1:2), goal);% exists in CLOSED setif loc_list(node_n, CLOSED, [1, 2])continueend% obstacleif map(node_n(1), node_n(2)) == 2continueendp_index = loc_list(cur_node(5: 6), CLOSED, [1, 2]);if p_indexnode_p = CLOSED(p_index, :);elsenode_p = 0;endif node_p ~= 0node_n = update_vertex(node_p, node_n);end% update OPEN setOPEN = [OPEN; node_n];endCLOSED = [cur_node; CLOSED];
end