摘要
针对移动机器人在多障碍物环境下路径规划时间长及路径冗余的问题,提出一种基于双向快速随机树和人工势场法算法的移动机器人路径规划方法。引入人工势场法来优化新节点的生成机制,提升算法的搜索效率,从而显著减少路径规划时间与路径长度。结合目标偏置策略来改进随机节点的生成方式,减少采样数量与采样时间。采用双向搜索策略进一步加速算法的收敛,缩短路径规划时间。仿真实验在复杂迷宫环境、凹型障碍物环境及U型陷阱环境中进行,结果显示,BI-RRT-APF算法相比传统RRT算法在路径长度上至少缩短了9.8%,在规划时间上至少减少了92.9%,有效提高了移动机器人的行驶效率。
To address the issues of long path planning time and path redundancy of mobile robots in multi-obstacle environments,a mobile robot path planning method based on the bidirectional rapid random tree and artificial potential field method(BI-RRT-APF)algorithm is proposed.First,the artificial potential field method is introduced to optimize the generation mechanism of new nodes,which improves the search efficiency of the algorithm,thus significantly reducing the path planning time and path length.At the same time,a target bias strategy is combined to improve the generation of random nodes and reduce the number of samples and sampling time.Finally,the two-way search strategy is used to further accelerate the convergence of the algorithm and shorten the path planning time.Simulation experiments were conducted in complex maze environments,concave obstacle environments,and U-shaped trap environments.The results show that compared to the traditional rapidly-exploring random tree(RRT)algorithm,the BI-RRT-APF algorithm shortens the path length by at least 9.8%and reduces the planning time by at least 92.9%,effectively improving the traveling efficiency of the mobile robot.
作者
朱子文
赵永娟
王中流
王海迪
周渊
ZHU Ziwen;ZHAO Yongjuan;WANG Zhongiu;WANG Haidi;ZHOU Yuan(School of Mechanical and Electrical Engineering,North University of China,Taiyuan 030051,China;Research Institute of Intelligent Weapon,North University of China,Taiyuan 030051,China)
出处
《火力与指挥控制》
北大核心
2025年第8期123-128,136,共7页
Fire Control & Command Control
基金
山西省2024年度研究生实践创新基金资助项目(2024SJ248)。
关键词
移动机器人
路径规划
快速拓展随机树算法
人工势场法
双向搜索策略
mobile robots
path planning
fast expanding random tree algorithm
artificial potential field method
bidirectional search strategy
