A Framework for Simultaneous Workpiece Registration in Robotic Machining Applications

被引:3
|
作者
Lloyd, Steffan [1 ]
Irani, Rishad [1 ]
Ahmadi, Mojtaba [1 ]
机构
[1] Carleton Univ, Dept Mech & Aerosp Engn, Ottawa, ON K1S 5B6, Canada
来源
2023 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, ICRA | 2023年
基金
加拿大自然科学与工程研究理事会;
关键词
FORCE CONTROL; CALIBRATION; POSITION; VISION; PARTS;
D O I
10.1109/ICRA48891.2023.10160445
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:5249 / 5255
页数:7
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