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.
作者
徐亚杰
王海星
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)
出处
《制造技术与机床》
北大核心
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)。
