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Lie-theory-based dynamic model identification of serial robots considering nonlinear friction and optimal excitation trajectory

Published online by Cambridge University Press:  16 October 2024

Ruiqing Luo Open the ORCID record for Ruiqing Luo [Opens in a new window] ,
Jianjun Yuan ,
Zhengtao Hu ,
Liang Du ,
Sheng Bao  and
Meijie Zhou
Ruiqing Luo
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Jianjun Yuan
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Zhengtao Hu
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Liang Du
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Sheng Bao*
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Meijie Zhou
Affiliation:
Shanghai Robotics Institute, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China Shanghai Robot Industrial Technology Institute, Shanghai, China
*
Corresponding author: Sheng Bao; Email: [email protected]
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Abstract

Accurate dynamic model is essential for the model-based control of robotic systems. However, on the one hand, the nonlinearity of the friction is seldom treated in robot dynamics. On the other hand, few of the previous studies reasonably balance the calculation time-consuming and the quality for the excitation trajectory optimization. To address these challenges, this article gives a Lie-theory-based dynamic modeling scheme of multi-degree-of-freedom (DoF) serial robots involving nonlinear friction and excitation trajectory optimization. First, we introduce two coefficients to describe the Stribeck characteristics of Coulomb and static friction and consider the dependency of friction on load torque, so as to propose an improved Stribeck friction model. Whereafter, the improved friction model is simplified in a no-load scenario, a novel nonlinear dynamic model is linearized to capture the features of viscous friction across the entire velocity range. Additionally, a new optimization algorithm of excitation trajectories is presented considering the benefits of three different optimization criteria to design the optimal excitation trajectory. On the basis of the above, we retrieve a feasible dynamic parameter set of serial robots through the hybrid least square algorithm. Finally, our research is supported by simulation and experimental analyses of different combinations on the seven-DoF Franka Emika robot. The results show that the proposed friction has better accuracy performance, and the modified optimization algorithm can reduce the overall time required for the optimization process while maintaining the quality of the identification results.

Keywords

dynamic modelnonlinear friction modelexcitation optimizationlie-theoryserial robots
Type
Research Article
Information
Robotica , Volume 42 , Issue 10 , October 2024 , pp. 3552 - 3569
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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