河南科技大学学报（自然科学版）2024，Vol.45Issue(3)：43-52,10.DOI:10.15926/j.cnki.issn1672-6871.2024.03.006
改进灰狼优化算法的草坪修剪机器人路径规划
Path Planning of lawn Mowing Robot Based on Improved Grey Wolf Algorithm
摘要
Abstract
To solve the problems of traditional grey wolf algorithm(GWO)being prone to local optima,slow convergence speed,high iteration times,and low weed removal efficiency when used for lawn trimming operations in full coverage path planning,a heuristic chaos operator grey wolf optimization algorithm(CGWO)is proposed.Based on the tent chaotic mapping,the CGWO is established by an adaptive parameter adjustment strategy in order to adjust the acceleration factor and various control parameters.This strategy enhances randomness in the search process,aiding the algorithm in escaping local optima and improving global search capability.Through simulation analysis,it was found that path cost,iteration times and time consumption of the CGWO algorithm is less than the GWO and particle swarm optimization(PSO)algorithms.Additionally,the generated path is smoother.Real vehicle experiments conducted in three types of lawn environments demonstrate that the CGWO algorithm is more effective than GWO and PSO algorithms.关键词
智能草坪修剪机器人/路径规划/灰狼优化算法/Tent混沌映射Key words
intelligent lawn trimming robot/path planning/grey wolf optimization algorithm/tent chaotic mapping分类
信息技术与安全科学引用本文复制引用
郭志军,王丁健,向中华,邱毅清,耿洋洋,王远,杜林林..改进灰狼优化算法的草坪修剪机器人路径规划[J].河南科技大学学报（自然科学版）,2024,45(3):43-52,10.基金项目
国家自然科学基金项目(51675163) （51675163）
