基于改进蝗虫优化算法的移动机器人路径规划  

Mobile robot path planning based on improved grasshopper optimization algorithm

作　　者：徐亚杰[1] 王海星[2] XU Yajie;WANG Haixing(School of Information Engineering,Zhengzhou Shengda University,Zhengzhou 451191,CHN;School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo 454003,CHN)

机构地区：[1]郑州升达经贸管理学院信息工程学院,河南郑州451191 [2]河南理工大学电气工程与自动化学院,河南焦作454003

出　　处：《制造技术与机床》2022年第2期14-18,共5页Manufacturing Technology & Machine Tool

基　　金：河南省高新技术领域科技攻关项目(172102210474);河南省高等教育教学改革研究与实践项目(2019SJGLX520)。

摘　　要：为提升蝗虫优化算法(GOA)在移动机器人路径规划中的应用效果,将基于Levy飞行的局部搜索策略和基于线性递减参数的随机跳出策略引入到GOA中,提出了改进蝗虫优化算法(IGOA)。相比于GOA,IGOA中的Levy飞行局部搜索策略增强了算法的随机性,线性递减参数的随机跳出策略降低了算法陷入局部最优的概率。移动机器人2种不同行驶环境的路径规划实例中,IGOA获得的结果更优。In order to improve the application effect of grasshopper optimization algorithm(GOA)in mobile robot path planning,improved grasshopper optimization algorithm(IGOA)was proposed by introducing levy flight local search strategy and linear declination parameters random jump strategy.The levy flight local search strategy and linear declination parameters random jump strategy IGOA respectively enhanced the randomness and reduced the probability of falling into the local optimum when compared with GOA.Two different driving environments of mobile robots path planning examples showed that IGOA obtained better results.

关 键 词：蝗虫优化算法 Levy飞行 移动机器人 路径规划 

分 类 号：TH165.3[机械工程—机械制造及自动化]