{"title":"基于神经网络的机器人参数计算","authors":"A. Lesewed, J. Kurek","doi":"10.1109/ROMOCO.2005.201411","DOIUrl":null,"url":null,"abstract":"The paper describes applications of recurrent neural network and back propagation learning method for calculation of mathematical model for PUMA 560 robot. The model is based on the Lagrange-Euler formulation and described by a set of nonlinear differential and algebraic equations. A numerical example has shown the comparison of neural model and robot manipulator.","PeriodicalId":142727,"journal":{"name":"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Calculation of robot parameters based on neural nets\",\"authors\":\"A. Lesewed, J. Kurek\",\"doi\":\"10.1109/ROMOCO.2005.201411\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper describes applications of recurrent neural network and back propagation learning method for calculation of mathematical model for PUMA 560 robot. The model is based on the Lagrange-Euler formulation and described by a set of nonlinear differential and algebraic equations. A numerical example has shown the comparison of neural model and robot manipulator.\",\"PeriodicalId\":142727,\"journal\":{\"name\":\"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROMOCO.2005.201411\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROMOCO.2005.201411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Calculation of robot parameters based on neural nets
The paper describes applications of recurrent neural network and back propagation learning method for calculation of mathematical model for PUMA 560 robot. The model is based on the Lagrange-Euler formulation and described by a set of nonlinear differential and algebraic equations. A numerical example has shown the comparison of neural model and robot manipulator.
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