海南大学学报（自然科学版）2025，Vol.43Issue(3)：275-281,7.DOI:10.15886/j.cnki.hdxbzkb.2024022201
基于改进遗传粒子群混合算法的机械臂时间最优轨迹规划
Time-optimal trajectory planning for manipulator based on improved genetic particle swarm optimization hybrid algorithm
摘要
Abstract
Aimed at the time-optimal trajectory planning problem of manipulator,in the report,an optimal trajectory planning method based on the improved genetic particle swarm optimization hybrid algorithm was proposed.The motion parameters of a six degree of freedom manipulator were used as the constraint conditions,a cubic uniform B-spline curve was used to construct the trajectory of the robotic arm.A penalty function was introduced to optimize the fitness function to improve the genetic algorithm in joint space.And an adaptive weight factor and Cauchy mutation operator were introduced to improve the particle swarm algorithm,and the improved particle swarm was integrated into the genetic algorithm as a crossover operator.The results showed that the solving accuracy of the improved genetic particle swarm optimization hybrid algorithm is higher than that of genetic algorithm and particle swarm algorithm,and its optimization efficiency has significantly improved compared to a single algorithm,algorithm,which validate the effectiveness of this method applied to trajectory planning of manipulator.关键词
六自由度机械臂/时间最优轨迹规划/粒子群算法Key words
six degree of freedom manipulator/time-optimal trajectory planning/particle swarm algorithm分类
通用工业技术引用本文复制引用
袁磊..基于改进遗传粒子群混合算法的机械臂时间最优轨迹规划[J].海南大学学报（自然科学版）,2025,43(3):275-281,7.基金项目
海南省自然科学基金项目(520RC535) （520RC535）
