A WLS-Based Step-by-Step Identification Method for Industrial Robot Dynamics Parameters

In order to improve the accuracy of robot dynamics parameter identification, this paper designs a step-by-step identification method based on weighted least squares. The robot dynamics model is first linearized to obtain the minimum parameter set. Subsequently, the friction model is built separately and experiments are designed to recognize the joint friction parameters first. Based on this, the excitation trajectory of finite term Fourier series is designed and optimized and data are collected. The joint moments obtained from the difference between the overall experimentally collected moments and the calculated friction moments are used to obtain the complete robot dynamics parameters based on weighted least squares identification. Comparison of the designed overall identification experiments shows that the total moment residuals of this method are reduced by 35.52% compared with the one-time identification method, which proves the effectiveness of this method.