A Two-Stage Payload Dynamic Parameter Identification Method for Interactive Industrial Robots With Large Components

被引：0

作者：

Liu, Mingxuan ^{[1
]}

Li, Pengcheng ^{[1
,2
]}

Duan, Jinjun ^{[1
,2
]}

Liu, Lunqian ^{[3
]}

Shen, Ye ^{[4
]}

Tian, Wei ^{[1
,2
]}

Ji, Yuqi ^{[3
]}

机构：

[1] Nanjing University of Aeronautics and Astronautics, College of Mechanical and Electrical Engineering, Nanjing,210016, China

[2] State Key Laboratory of Intelligent Manufacturing System Technology for Complex Products, Beijing,100854, China

[3] Shanghai Aircraft Manufacturing Company, Shanghai,200120, China

[4] Shanghai Aerospace Electronic Technology Research Institute, Shanghai,201109, China

来源：

IEEE Transactions on Automation Science and Engineering | 2025年 / 22卷

基金：

中国国家自然科学基金;

关键词：

Assembly machines - Collaborative robots - Religious buildings - Robotic assembly;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Taking human-robot collaborative assembly as an example, the methods based on contact forces can improve the assembly efficiency of industrial robots with large components in industrial manufacturing. However, due to the large size, high payload, assembly accuracy and dynamic changes in grip position, accurately estimating the contact forces between the payload and the operator becomes challenging when handling these large components. In this paper, a two-stage method is proposed for payload dynamic parameter identification. The parameter identification equation in the sensor coordinate system is initially established. Furthermore, the identification model of recursive restricted total least squares (RRTLS) based on total least squares (TLS) is constructed to achieve low-consumption online identification. According to the assembly requirements and payload characteristics, the posture coordinate system is designed for safety, including the feasible workspace for the robot. Subsequently, the static identification postures and dynamic excitation trajectory are planned to obtain static values and dynamic inertial parameters. In the end, a high-payload human-robot collaborative assembly system is built to validate the proposed method. Experimental results show that compared with the existing methods, the proposed approach can effectively identify and compensate the payload, leading to more accurate external force sensing. © 2004-2012 IEEE.

引用

页码：13871 / 13883