{"title":"Identification of Quasi-linear Dynamic Model with Dead Zone for Mobile Robot with Differential Drive","authors":"E. Mendes, A. Medeiros","doi":"10.1109/LARS.2010.36","DOIUrl":null,"url":null,"abstract":"This note deals with the identification of a mobile robot with differential drive. The robot system is modeled by two MISO Hammer stein systems with input dead zones. The robot dynamic model is based on the traveled distance increment instead of the robot coordinates, making the model linear and allowing the application of classical methods of identification. Both parameters of linear and nonlinear blocks are estimated simultaneously through application of recursive least squares. Our main contribution is to use simple identification techniques to recursively estimate the linear and non-linear parameters of the robot system, that may vary over the time. The feasibility of the method is demonstrated by examples using both simulated and real robot.","PeriodicalId":268931,"journal":{"name":"2010 Latin American Robotics Symposium and Intelligent Robotics Meeting","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Latin American Robotics Symposium and Intelligent Robotics Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LARS.2010.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This note deals with the identification of a mobile robot with differential drive. The robot system is modeled by two MISO Hammer stein systems with input dead zones. The robot dynamic model is based on the traveled distance increment instead of the robot coordinates, making the model linear and allowing the application of classical methods of identification. Both parameters of linear and nonlinear blocks are estimated simultaneously through application of recursive least squares. Our main contribution is to use simple identification techniques to recursively estimate the linear and non-linear parameters of the robot system, that may vary over the time. The feasibility of the method is demonstrated by examples using both simulated and real robot.