{"title":"A Research on Particle Swarm Optimization and Its Application in Robot Manipulators","authors":"Gang Huang, Dehua Li, Jie Yang","doi":"10.1109/PACIIA.2008.226","DOIUrl":null,"url":null,"abstract":"Trajectory planning problem (TPP) of robot manipulator is a highly constrained and nonlinear optimization problem, aims to minimize the total path motion associated with obstacle avoidance. Based on some certain constraints listed in this paper. A particle swarm optimization (PSO) based algorithm is put forward to solve this issue. The proposed algorithm consists of a hybrid approach regarding SA. Then the SA-PSO has been implemented on a tested example. In addition, a conventional algorithms, namely A* Algorithm (AA), is introduced to make a comparison with SA-PSO. The computational results show that the developed algorithm is computationally better (in terms of the convergence time and precision of solution) than the other method.","PeriodicalId":275193,"journal":{"name":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","volume":"200 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIIA.2008.226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Trajectory planning problem (TPP) of robot manipulator is a highly constrained and nonlinear optimization problem, aims to minimize the total path motion associated with obstacle avoidance. Based on some certain constraints listed in this paper. A particle swarm optimization (PSO) based algorithm is put forward to solve this issue. The proposed algorithm consists of a hybrid approach regarding SA. Then the SA-PSO has been implemented on a tested example. In addition, a conventional algorithms, namely A* Algorithm (AA), is introduced to make a comparison with SA-PSO. The computational results show that the developed algorithm is computationally better (in terms of the convergence time and precision of solution) than the other method.
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