改进RRT结合B样条的移动机器人路径规划研究  

Research on path planning of mobile robot based on improved RRT and B-spline

作　　者：陈都 侯明[1] 张学东 Chen Du;Hou Ming;Zhang Xuedong(School of Automation,Beijing Information Science and Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学自动化学院,北京100192

出　　处：《电子测量技术》2022年第23期38-44,共7页Electronic Measurement Technology

基　　金：国家自然科学基金(61971048);北京信息科技大学重点培育项目(5212110927)资助。

摘　　要：针对快速扩展随机树(RRT)算法在移动机器人路径规划中的时间过长、路径冗长曲折且平滑度较差等问题,提出一种新的采样节点生成和路径节点选取的改进型RRT算法。该算法以融合采样点概率和目标点引力的方式,再结合动态变随机步长的策略,加快了向目标点的扩展,降低了规划时间;最后为完成路径优化,对利用正向寻优和二次选取过后的路径节点,采用B样条函数进行处理,综合改善了路径的长度及其平滑性。在仿真实验中分别与传统RRT算法,P-RRT算法进行比较,实验结果表明:所提算法在路径长度,规划时间以及路径节点个数均有一定优化,且路径平滑性得到了有效提升。To address the problems of the rapidly-exploring random trees(RRT) algorithm in mobile robot path planning including time cost, long and tortuous path, and poor smoothness, an improved RRT algorithm of new sampling node generation and path node selection is proposed. The algorithm combines the probability of sampling points and the gravitation of the target point, and dynamically changes the random step size, thus accelerating the expansion to the target point and reducing the planning time. Finally, to complete the path optimization, the path nodes obtained after the forward optimization and the secondary selection are processed using the B-spline function, which comprehensively improves the path in terms of length and smoothness. The proposed algorithm has been compared with traditional RRT algorithm and P-RRT algorithm in the simulation experiments, whose results show that the proposed algorithm has improved the path length, planning time and the number of path nodes to a certain amount, and effectively the path smoothness.

关 键 词：RRT算法 移动机器人 路径优化 二次选取 B样条 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]