Maximum Allowable TCF Calibration Error for Robotic Pose Servoing

被引:1
|
作者
Hou, Jun [1 ,2 ]
Xing, Shiyu [1 ,2 ]
Ma, Yunkai [1 ,2 ]
Jing, Fengshui [1 ,2 ]
Tan, Min [3 ]
机构
[1] Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
[3] Chinese Acad Sci, Inst Automat, Key Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2025年 / 10卷 / 02期
基金
中国国家自然科学基金;
关键词
Calibration; Robots; Robot kinematics; Stars; Assembly; Servomotors; Robustness; Measurement uncertainty; Accuracy; Visualization; Formal methods in robotics and automation; calibration and identification; assembly;
D O I
10.1109/LRA.2024.3522840
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Robotic pose servoing aims to move the robot end-effector to the target pose. Closed-loop servo systems can tolerate a small TCF (tool control frame) calibration error and accurately reach the target pose through multiple pose measurements and pose adjustments. However, the maximum allowable TCF calibration error remains an open question. This paper demonstrates that the necessary condition for robotic pose servoing is a TCF calibration error angle of less than 60 degrees, with no limit on the translational component of the TCF calibration error. Next, an improved pose servoing method is proposed to address the conflict between the large TCF error and the limited robot workspace. This method introduces a scaling factor to limit the adjustment range within the robot workspace, ensuring greater robustness. Finally, robot-assisted cabin docking is selected as an experimental validation case. Simulation and physical experiments validate the maximum allowable TCF calibration error. Comparative experiments confirm the robustness of the improved pose servoing method, achieving cabin docking despite significant TCF calibration errors.
引用
收藏
页码:1744 / 1751
页数:8
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