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A novel parameter identification method for flexible-joint robots using input torque and motor-side motion data

Published online by Cambridge University Press:  14 February 2022

Pu Zhao Open the ORCID record for Pu Zhao [Opens in a new window]
Pu Zhao*
Affiliation:
School of Mechanical and Electrical Engineering, Henan University of Technology, Zheng Zhou 450001, China
*
*Corresponding author. E-mail: [email protected]
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Abstract

The traditional identification methods of industrial robots are based on Inverse Dynamic Identification Model (IDIM). Based on the model, input torque, motor-side and link-side motion data are necessary when joint flexibilities are considered. However, it is often unavailable or expensive to general robots which are not equipped with link-side sensors. To solve the problem, a novel dynamic parameter identification method, which only employ input torque and motor-side motion data, is proposed in this report. Based on motor-side dynamics, link-side dynamics are modified as high-order nonlinear functions of input torque and motor-side motion. Then, through different trajectory-load groups and high-order observers, the nonlinear equations can be solved, and dynamic parameters can be estimated with short operation time. The selection rules of the trajectory-load groups are then discussed based on simulation results, so as to promote estimation results. Finally, experiments are conducted to verify the proposed method and exhibit the selection rules of observer gains. As shown in the report, except viscous friction parameters, identification difference between the IDM-based methods and the proposed one is less than 9%.

Keywords

flexible-joint robotdynamic modelobserverparameter identificationnonlinear equations
Type
Research Article
Information
Robotica , Volume 40 , Issue 9 , September 2022 , pp. 3077 - 3087
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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