{"title":"基于瞬态递归神经网络控制器的目标定向运动生成","authors":"R. F. Reinhart, Jochen J. Steil","doi":"10.1109/AT-EQUAL.2009.31","DOIUrl":null,"url":null,"abstract":"We introduce a control framework based on a recurrent neural network for goal-directed movement generation. We exploit the network dynamics to implement a nonlinear task space controller. Efficient online learning and execution of the network makes the proposed approach adaptive and real-time capable. We achieve reliable and excellent generalization for the 7-DOF redundant PA-10 robot arm in simulation.","PeriodicalId":407640,"journal":{"name":"2009 Advanced Technologies for Enhanced Quality of Life","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Goal-Directed Movement Generation with a Transient-Based Recurrent Neural Network Controller\",\"authors\":\"R. F. Reinhart, Jochen J. Steil\",\"doi\":\"10.1109/AT-EQUAL.2009.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a control framework based on a recurrent neural network for goal-directed movement generation. We exploit the network dynamics to implement a nonlinear task space controller. Efficient online learning and execution of the network makes the proposed approach adaptive and real-time capable. We achieve reliable and excellent generalization for the 7-DOF redundant PA-10 robot arm in simulation.\",\"PeriodicalId\":407640,\"journal\":{\"name\":\"2009 Advanced Technologies for Enhanced Quality of Life\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Advanced Technologies for Enhanced Quality of Life\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AT-EQUAL.2009.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Advanced Technologies for Enhanced Quality of Life","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AT-EQUAL.2009.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Goal-Directed Movement Generation with a Transient-Based Recurrent Neural Network Controller
We introduce a control framework based on a recurrent neural network for goal-directed movement generation. We exploit the network dynamics to implement a nonlinear task space controller. Efficient online learning and execution of the network makes the proposed approach adaptive and real-time capable. We achieve reliable and excellent generalization for the 7-DOF redundant PA-10 robot arm in simulation.
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