{"title":"Time optimal trajectory planning of five degrees of freedom manipulator based on PSO algorithm","authors":"Zhengshuai Jiang, Qizhi Zhang","doi":"10.1109/ICMSP55950.2022.9858972","DOIUrl":null,"url":null,"abstract":"According to the kinematic constraints of the manipulator, a time-optimized 3-5-3 polynomial interpolation algorithm based on particle swarm optimization in joint space is proposed, which solves the shortcomings of polynomial interpolation trajectory planning with high order and no convex hull. Particle swarm optimization is simple in structure, easy to implement, and easy to adjust parameters. It directly selects the polynomial interpolation time as a variable, searches in the target space, and obtains the shortest interpolation time under the specified speed constraint. The simulation is carried out on the experimental platform, and compared with the traditional 3-5-3 polynomial interpolation of position, velocity and acceleration curves, it is proved that the method can achieve shorter running time and better stability of the manipulator.","PeriodicalId":114259,"journal":{"name":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","volume":"105 5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Intelligent Control, Measurement and Signal Processing (ICMSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSP55950.2022.9858972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
According to the kinematic constraints of the manipulator, a time-optimized 3-5-3 polynomial interpolation algorithm based on particle swarm optimization in joint space is proposed, which solves the shortcomings of polynomial interpolation trajectory planning with high order and no convex hull. Particle swarm optimization is simple in structure, easy to implement, and easy to adjust parameters. It directly selects the polynomial interpolation time as a variable, searches in the target space, and obtains the shortest interpolation time under the specified speed constraint. The simulation is carried out on the experimental platform, and compared with the traditional 3-5-3 polynomial interpolation of position, velocity and acceleration curves, it is proved that the method can achieve shorter running time and better stability of the manipulator.