@inproceedings{7ced95088c084c7cb8fd2d415d77483c,
title = "A Study of KUKA Robot Joint Error Modeling and Experimental Verification",
abstract = "Industrial robots have great advantages in the processing of large and complex components in the aerospace field, but the lack of robot joint stiffness results in poor processing accuracy. This paper first analyzes the stiffness of the robot's joints and establishes a joint error model; Secondly, the kinematics modeling of the KUKA KR 600 robot was carried out by using the Modified D-H method, the established model was calibrated by MATLAB, and the Jacobian matrix J was calculated; Thirdly, the stiffness of the robot joints was identified through experiments; Finally, the joint error model validation was carried out. Results showed that the relative errors between the predicted and actual measured values in the x, y and z directions are 21.39%, 17.01% and 14.46% respectively. It is proved that the established joint error model shows large potential in predicting the deformation of the robot end.",
keywords = "Industrial robot, Joint error, Joint stiffness, Modified D-H model",
author = "Zhibo Zhang and Li Jiao and Tianyang Qiu and Wenhua Shen and Pei Yan and Xibin Wang",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE. All rights reserved.; 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022 ; Conference date: 25-02-2022 Through 27-02-2022",
year = "2022",
doi = "10.1117/12.2641330",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ligu Zhu",
booktitle = "2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022",
address = "United States",
}