摘要
针对未知环境中的水下无人航行器路径规划问题,笔者提出了一种改进的快速扩展随机树(RRT)算法。一方面针对传统RRT算法不能在未知环境中应用的问题,将滚动规划的思想与RRT算法相结合,通过不同情况下的子目标点选取策略选取合适的子目标点,并利用RRT算法规划前往子目标点的路径,实现了水下无人航行器的在线实时路径规划;另一方面,为了减少传统RRT算法的冗余搜索量,引入评价函数,使随机树的扩展方向具有目的性,提高了路径规划效率。最后,通过仿真实验验证了改进RRT算法的有效性。
An improved fast extended random tree (RRT) algorithm is proposed to solve the path planning problem of unmanned underwater vehicle (UUV) in unknown environment.On the one hand,aiming at the problem that the traditional RRT algorithm can not be applied in unknown environment,the idea of rolling planning is combined with RRT algorithm,the appropriate sub target points are selected through the sub target point selection strategy in different situations,and the path to the sub target point is planned by using RRT algorithm,so as to realize the on-line real-time path planning of AUV;on the other hand,in order to reduce the traditional RRT,it is necessary to select the appropriate sub target points by using the RRT algorithm The redundant search amount of the algorithm and the introduction of evaluation function make the expansion direction of the random tree purposeful and improve the efficiency of path planning.Finally,the effectiveness of the improved RRT algorithm is verified by simulation experiments.
作者
张伟
孙毅
Zhang Wei;Sun Yi(School of Automation,Harbin Engineering University,Harbin Heilongjiang 150001,China)
出处
《信息与电脑》
2020年第12期74-77,共4页
Information & Computer
基金
多自主水下无人航行器编队协调一致性控制研究(项目编号:51609046)。
关键词
未知环境
水下无人航行器
滚动规划
改进RRT算法
unknown environment
underwater unmanned aerial vehicle
rolling planning
improved RRT algorithm
