摘要
移动机器人路径规划是机器人研究中最关键的技术之一,机器人进行最优的路径规划是其中的难点。文章以目前对移动机器人路径规划的研究现状为基础,通过具体分析与研究,将现有成果进行归纳总结、深入探讨;并依据基本原理与应用场景的不同,将算法划分为智能仿生、几何模型搜索、虚拟势场、强化学习4类;通过对每类算法的分析可得出各算法的优缺点以及主要适用场景,并通过多种不同算法相互结合的方式来解决移动机器人路径规划的问题。该文为动态环境下移动机器人路径规划的研究奠定了一定的理论基础。
Path planning of mobile robots is one of the most critical technologies in robot research.Especially in complex and changeable dynamic environment,how to optimize the path planning of mobile robots has become a difficult problem.Based on the current research status of mobile robot path planning,this paper summarizes and discusses the existing achievements through specific analysis and research.According to the basic principles of the algorithms and the different application scenarios,they are divided into four categories:intelligent bionics,geometric model search,virtual potential field and reinforcement learning.Through the analysis of each kind of algorithm,the advantages and disadvantages of each kind of algorithm as well as the main applicable scenarios are obtained.The idea of combining different algorithms is used to solve the problem of mobile robot path planning,which lays a foundation for the research of mobile robot path planning in dynamic environment.
作者
张艳
张明路
蒋志宏
吕晓玲
ZHANG Yan;ZHANG Minglu;JIANG Zhihong;LYU Xiaoling(School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China)
出处
《合肥工业大学学报（自然科学版）》
CAS
北大核心
2020年第10期1297-1306,共10页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金资助项目(61733001)
河北省自然科学基金和重点基础研究专项资助项目(E2018202338)。
关键词
动态环境
路径规划
移动机器人
算法分类与结合
dynamic environment
path planning
mobile robot
classification and combination of algorithms
