{"title":"通过导数CESTAC方法验证参数识别技术","authors":"N. Marcassus, P. Vandanjon, A. Janot, M. Gautier","doi":"10.1109/CIRA.2007.382898","DOIUrl":null,"url":null,"abstract":"Parametric identification consists in estimating the values of physical parameters of robotic systems. The most popular methods consist in using the least squares regression because of their simplicity. However, we know that these techniques are not intrinsically robust. An alternative consists in justifying the use of the LS technique. This paper focuses on this issue and introduces a derivation of the CESTAC method which will be applied to a 6 degrees of freedom (DOF) serial robot.","PeriodicalId":301626,"journal":{"name":"2007 International Symposium on Computational Intelligence in Robotics and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Validation of a Parametric Identification Technique through a Derivative CESTAC Method\",\"authors\":\"N. Marcassus, P. Vandanjon, A. Janot, M. Gautier\",\"doi\":\"10.1109/CIRA.2007.382898\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Parametric identification consists in estimating the values of physical parameters of robotic systems. The most popular methods consist in using the least squares regression because of their simplicity. However, we know that these techniques are not intrinsically robust. An alternative consists in justifying the use of the LS technique. This paper focuses on this issue and introduces a derivation of the CESTAC method which will be applied to a 6 degrees of freedom (DOF) serial robot.\",\"PeriodicalId\":301626,\"journal\":{\"name\":\"2007 International Symposium on Computational Intelligence in Robotics and Automation\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Symposium on Computational Intelligence in Robotics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIRA.2007.382898\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Symposium on Computational Intelligence in Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIRA.2007.382898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Validation of a Parametric Identification Technique through a Derivative CESTAC Method
Parametric identification consists in estimating the values of physical parameters of robotic systems. The most popular methods consist in using the least squares regression because of their simplicity. However, we know that these techniques are not intrinsically robust. An alternative consists in justifying the use of the LS technique. This paper focuses on this issue and introduces a derivation of the CESTAC method which will be applied to a 6 degrees of freedom (DOF) serial robot.