{"title":"基于神经网络补偿的稳定视觉伺服","authors":"G. Loreto, Wen Yu, R. Garrido","doi":"10.1109/ISIC.2001.971505","DOIUrl":null,"url":null,"abstract":"We propose a stable 2D visual servoing algorithm for planar robot manipulators. We assume that gravity and friction are unknown and that there exists modeling errors in the vision system. By using a radial basis function neural network, it is shown that these uncertainties can be compensated. We prove that without or with unmodeled dynamics, the 2D visual servoing with neural networks compensation is Lyapunov stable.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Stable visual servoing with neural network compensation\",\"authors\":\"G. Loreto, Wen Yu, R. Garrido\",\"doi\":\"10.1109/ISIC.2001.971505\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a stable 2D visual servoing algorithm for planar robot manipulators. We assume that gravity and friction are unknown and that there exists modeling errors in the vision system. By using a radial basis function neural network, it is shown that these uncertainties can be compensated. We prove that without or with unmodeled dynamics, the 2D visual servoing with neural networks compensation is Lyapunov stable.\",\"PeriodicalId\":367430,\"journal\":{\"name\":\"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.2001.971505\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.2001.971505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stable visual servoing with neural network compensation
We propose a stable 2D visual servoing algorithm for planar robot manipulators. We assume that gravity and friction are unknown and that there exists modeling errors in the vision system. By using a radial basis function neural network, it is shown that these uncertainties can be compensated. We prove that without or with unmodeled dynamics, the 2D visual servoing with neural networks compensation is Lyapunov stable.