基于人工势场法的多机器人协同避障  

Multi-robot Collaborative Obstacle Avoidance Based on Artificial Potential Field Method

作　　者：陈骏岭 秦小麟[1] 李星罗 周杨淏 鲍斌国 CHEN Jun-ling;QIN Xiao-lin;LI Xing-luo;ZHOU Yang-hao;BAO Bin-guo(College of Computer Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

机构地区：[1]南京航空航天大学计算机科学与技术学院,南京210016

出　　处：《计算机科学》2020年第11期220-225,共6页Computer Science

基　　金：国家自然科学基金(61373015,61728204)。

摘　　要：近年来,随着社会对机器人关注度的增加,移动机器人技术逐渐成为研究热点。机器人避障是移动机器人学中重要的研究课题,也是移动机器人面临的基本问题之一。针对多机器人的应用场景,在充分分析现有机器人避障算法的基础上,优化人工势场法,提出多机器人避障算法MPF(Multi-Robot Artificial Potential Field Method)和编队避障算法AOA(Advanced Obstacle Avoidance Method)。MPF算法优化了人工势场法存在局部最小值点的问题,提高了机器人到达目标点的概率;AOA算法结合现有的编队避障算法来提高机器人编队避障的效率。最后,分别为MPF算法和AOA算法设计不同的实验环境,实验结果表明,在障碍物复杂情况不同的环境中MPF算法可以有效且高效地引导机器人到达目标点;在不同的环境复杂度和机器人数量下,AOA算法能够提供高效稳定的编队避障。In recent years,with the increasing attention paid to robots,mobile robot technology has gradually become a research hotspot.Robot obstacle avoidance is an important research topic in mobile robotics,and it is one of the basic problems faced by mobile robots.Aiming at the application scenario of multi-robot,the artificial potential field method is optimized based on the full analysis of the existing robot obstacle avoidance algorithms,and the multi-robot obstacle avoidance algorithm MPF and formation obstacle avoidance algorithm AOA are proposed.MPF algorithm optimizes the problem of local minimum point in artificial potential field method,and increases the probability of robot reaching the target point.AOA algorithm combines with the existing formation obstacle avoidance algorithm to improve the efficiency of formation obstacle avoidance.Finally,different experimental environments are designed for MPF and AOA algorithms respectively.Experiment results show that,in different complex obstacle environments,MPF algorithm can guide the robot to the target point effectively and efficiently,while AOA algorithm can provide efficient and stable formation obstacle avoidance under different environmental complexity and number of robots.

关 键 词：人工势场法 虚拟目标点 移动机器人 轨迹跟随 移动障碍物 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]