机械科学与技术2024，Vol.43Issue(3)：394-401,8.DOI:10.13433/j.cnki.1003-8728.20220286
改进灰狼算法在搬运机器人轨迹规划中的应用
Application of Improved Gray Wolf Algorithm in Trajectory Planning of Pallet Handling Robot
摘要
Abstract
In order to improve the running stability of the pallet handling robot,an optimal trajectory planning method for robot acceleration based on the improved gray wolf algorithm is proposed.Aiming at the problems of local convergence and insufficient optimization performance of gray wolf algorithm,the Logistic-Tent chaotic map is introduced to optimize the initial population;the differential optimization algorithm is introduced to improve the global search ability;the elimination evolution mechanism is introduced to optimize the population structure and improve the optimization performance in all-round way.Compared with the standard gray wolf algorithm and the particle swarm algorithm,simulation results show that improved gray wolf algorithm has better convergence speed and algorithm accuracy in different types of test functions.In the application of the trajectory planning of the handling robot,after the optimization of the algorithm,the maximum joint angular acceleration of the robot is reduced by 44.11%,which greatly improves the running stability.关键词
搬运机器人/轨迹规划/加速度/灰狼算法Key words
handling robot/trajectory planning/acceleration/gray wolf algorithm分类
信息技术与安全科学引用本文复制引用
张攀,刘雨晗,张威..改进灰狼算法在搬运机器人轨迹规划中的应用[J].机械科学与技术,2024,43(3):394-401,8.基金项目
国家自然科学基金民航联合基金重点项目(U2033208)、中央高校基本科研业务费项目(3122023018)及天津市研究生科研创新项目(2021YJSS122) （U2033208）
