{"title":"基于PSO-RBF网络的PUMA560机械手运动学逆解方法","authors":"Zhe Ming Li, Chun Gui Li, S. Lv","doi":"10.1109/ICNC.2012.6234507","DOIUrl":null,"url":null,"abstract":"This paper describes the use of particle swarm algorithm and k-nearest neighbor method to optimize the process of radial basis function (RBF) network and we use the Denavit-Hartenberg (DH) method to research PUMA560 robotics, the results of the forward kinematics is derived as the RBF network training samples. We use six identical RBF network of twelve-input, single output, to achieve a PUMA560 inverse kinematics calculation. Simulation results show that the results obtained with this method has high accuracy and fast convergence.","PeriodicalId":404981,"journal":{"name":"2012 8th International Conference on Natural Computation","volume":"203 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A method for solving inverse kinematics of PUMA560 manipulator based on PSO-RBF network\",\"authors\":\"Zhe Ming Li, Chun Gui Li, S. Lv\",\"doi\":\"10.1109/ICNC.2012.6234507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the use of particle swarm algorithm and k-nearest neighbor method to optimize the process of radial basis function (RBF) network and we use the Denavit-Hartenberg (DH) method to research PUMA560 robotics, the results of the forward kinematics is derived as the RBF network training samples. We use six identical RBF network of twelve-input, single output, to achieve a PUMA560 inverse kinematics calculation. Simulation results show that the results obtained with this method has high accuracy and fast convergence.\",\"PeriodicalId\":404981,\"journal\":{\"name\":\"2012 8th International Conference on Natural Computation\",\"volume\":\"203 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 8th International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2012.6234507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 8th International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2012.6234507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A method for solving inverse kinematics of PUMA560 manipulator based on PSO-RBF network
This paper describes the use of particle swarm algorithm and k-nearest neighbor method to optimize the process of radial basis function (RBF) network and we use the Denavit-Hartenberg (DH) method to research PUMA560 robotics, the results of the forward kinematics is derived as the RBF network training samples. We use six identical RBF network of twelve-input, single output, to achieve a PUMA560 inverse kinematics calculation. Simulation results show that the results obtained with this method has high accuracy and fast convergence.
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