In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ-RRT with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.

中文翻译：

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NPQ-RRT：用于混合路径规划的改进RRT方法

近年来，机器人的路径规划一直是研究的热点，多机器​​人的形成在我们的生活中具有实际的应用前景。本文提出了一种应用于机器人编队的混合路径规划算法。改进的快速探索随机树算法PQ-RRT具有新的距离评估功能的算法用作全局规划算法，以生成初始全局路径。确定的父节点和子节点分别用作本地规划算法的起点和目标点。动态窗口方法用作局部规划算法，以避免动态障碍。同时，该算法限制了机器人在地层内部的移动，以避免内部碰撞。通过包含地层碰撞可能性的评估函数选择局部最优路径。因此，通过混合路径规划算法，多个移动机器人可以在具有动态和静态障碍的复杂环境中快速安全地到达全局目标点。