{"title":"基于混合PSOGSA算法的3R机械手优化设计","authors":"S. Panda, D. Mishra, B. B. Biswal","doi":"10.1504/IJMRS.2021.10037763","DOIUrl":null,"url":null,"abstract":"Larger workspace volume is one of the most important objectives in the optimum design of robot manipulator. In the present study, the workspace volume of a 3R manipulator has been maximised. The nonlinear constrained optimisation problem has been solved using the particle swarm optimisation (PSO) and a hybrid PSO and gravitational search algorithm (GSA). The proposed algorithm combines the search method of PSO and GSA with enhanced exploration ability to achieve higher workspace volume as compared to the established available results. Further, the total void cross section area has been estimated and a quantitative analysis of the results has been made to identify the key influencing kinematic parameters and prioritise the constraints. Applications of the hybrid algorithm on two industrial manipulators are presented as case studies. An important implication of this article is that the proposed hybrid algorithm provides encouraging result in terms of objective function values and CPU time.","PeriodicalId":344520,"journal":{"name":"International Journal of Mechanisms and Robotic Systems","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimum design of 3R manipulator using hybrid PSOGSA algorithm\",\"authors\":\"S. Panda, D. Mishra, B. B. Biswal\",\"doi\":\"10.1504/IJMRS.2021.10037763\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Larger workspace volume is one of the most important objectives in the optimum design of robot manipulator. In the present study, the workspace volume of a 3R manipulator has been maximised. The nonlinear constrained optimisation problem has been solved using the particle swarm optimisation (PSO) and a hybrid PSO and gravitational search algorithm (GSA). The proposed algorithm combines the search method of PSO and GSA with enhanced exploration ability to achieve higher workspace volume as compared to the established available results. Further, the total void cross section area has been estimated and a quantitative analysis of the results has been made to identify the key influencing kinematic parameters and prioritise the constraints. Applications of the hybrid algorithm on two industrial manipulators are presented as case studies. An important implication of this article is that the proposed hybrid algorithm provides encouraging result in terms of objective function values and CPU time.\",\"PeriodicalId\":344520,\"journal\":{\"name\":\"International Journal of Mechanisms and Robotic Systems\",\"volume\":\"125 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Mechanisms and Robotic Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJMRS.2021.10037763\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Mechanisms and Robotic Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMRS.2021.10037763","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimum design of 3R manipulator using hybrid PSOGSA algorithm
Larger workspace volume is one of the most important objectives in the optimum design of robot manipulator. In the present study, the workspace volume of a 3R manipulator has been maximised. The nonlinear constrained optimisation problem has been solved using the particle swarm optimisation (PSO) and a hybrid PSO and gravitational search algorithm (GSA). The proposed algorithm combines the search method of PSO and GSA with enhanced exploration ability to achieve higher workspace volume as compared to the established available results. Further, the total void cross section area has been estimated and a quantitative analysis of the results has been made to identify the key influencing kinematic parameters and prioritise the constraints. Applications of the hybrid algorithm on two industrial manipulators are presented as case studies. An important implication of this article is that the proposed hybrid algorithm provides encouraging result in terms of objective function values and CPU time.