{"title":"机器人加工中工件同步配准的框架","authors":"Steffan Lloyd, R. Irani, M. Ahmadi","doi":"10.1109/ICRA48891.2023.10160445","DOIUrl":null,"url":null,"abstract":"This article presents a novel framework called Simultaneous Registration and Machining (SRAM), a generalized method to improve workpiece registration using real-time acquired data in robotic contouring applications. The method allows for online corrections to the toolpath, while a live covariance estimate is simultaneously leveraged to adaptively tune the force controller aggressively when uncertainty is high, but conservatively otherwise to minimize chatter and instability. The SRAM framework is validated in simulation and shown to significantly reduce the path corrections required from the force controller, while correctly predicting optimal controller tuning adaptations. The SRAM method is proposed to improve force control stability, increase peripheral accuracy, smooth surface finish, and reduce cycle times in contouring applications.","PeriodicalId":360533,"journal":{"name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Framework for Simultaneous Workpiece Registration in Robotic Machining Applications\",\"authors\":\"Steffan Lloyd, R. Irani, M. Ahmadi\",\"doi\":\"10.1109/ICRA48891.2023.10160445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a novel framework called Simultaneous Registration and Machining (SRAM), a generalized method to improve workpiece registration using real-time acquired data in robotic contouring applications. The method allows for online corrections to the toolpath, while a live covariance estimate is simultaneously leveraged to adaptively tune the force controller aggressively when uncertainty is high, but conservatively otherwise to minimize chatter and instability. The SRAM framework is validated in simulation and shown to significantly reduce the path corrections required from the force controller, while correctly predicting optimal controller tuning adaptations. The SRAM method is proposed to improve force control stability, increase peripheral accuracy, smooth surface finish, and reduce cycle times in contouring applications.\",\"PeriodicalId\":360533,\"journal\":{\"name\":\"2023 IEEE International Conference on Robotics and Automation (ICRA)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Robotics and Automation (ICRA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRA48891.2023.10160445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA48891.2023.10160445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Framework for Simultaneous Workpiece Registration in Robotic Machining Applications
This article presents a novel framework called Simultaneous Registration and Machining (SRAM), a generalized method to improve workpiece registration using real-time acquired data in robotic contouring applications. The method allows for online corrections to the toolpath, while a live covariance estimate is simultaneously leveraged to adaptively tune the force controller aggressively when uncertainty is high, but conservatively otherwise to minimize chatter and instability. The SRAM framework is validated in simulation and shown to significantly reduce the path corrections required from the force controller, while correctly predicting optimal controller tuning adaptations. The SRAM method is proposed to improve force control stability, increase peripheral accuracy, smooth surface finish, and reduce cycle times in contouring applications.