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10 November 2022 A study of KUKA robot joint error modeling and experimental verification
Zhibo Zhang, Li Jiao, Tianyang Qiu, Wenhua Shen, Pei Yan, Xibin Wang
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Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 1234838 (2022) https://doi.org/10.1117/12.2641330
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China
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.
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Zhibo Zhang, Li Jiao, Tianyang Qiu, Wenhua Shen, Pei Yan, and Xibin Wang "A study of KUKA robot joint error modeling and experimental verification", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 1234838 (10 November 2022); https://doi.org/10.1117/12.2641330
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KEYWORDS
Kinematics
Error analysis
Modeling
MATLAB
Robotics
Aerospace engineering
Robotic systems
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