Abstract
Based on the established serial 6-DOF robot calibration experiment platform, this paper aims to analyze and compare the effects of four error compensation methods, which are pseudotarget iteration-based error compensation method with three different forms and the Newton–Raphson-based error compensation method. Firstly, the pose error model of the serial robot is established based on the M-DH model in this paper. The calibration results show that the accuracy of the Staubli TX60 robot has been greatly improved. The average comprehensive position accuracy is increased by 88.7%, and the average comprehensive attitude accuracy is increased by 56.6%. Secondly, the principles of the four error compensation methods are discussed, and the effectiveness of the four error compensation methods are compared through experiments. The results show that the four error compensation methods can achieve error compensation well. The compensation accuracy is consistent with the identification accuracy of the kinematic model. The pseudotarget iteration with differential form has the best performance by the comprehensive consideration of accuracy and computational efficiency. Error compensation determines whether the accuracy of the identified model can be achieved. This paper presents a systematic experimental validation research on the effectiveness of four error compensation methods, which provides a reliable reference for the kinematic error compensation of industrial robots.
Highlights
Based on the established serial 6-DOF robot calibration experiment platform, this paper aims to analyze and compare the effects of four error compensation methods, which are pseudotarget iteration-based error compensation method with three different forms and the Newton–Raphson-based error compensation method
The pose error model of the serial robot is established based on the M-DH model in this paper. e calibration results show that the accuracy of the Staubli TX60 robot has been greatly improved. e average comprehensive position accuracy is increased by 88.7%, and the average comprehensive attitude accuracy is increased by 56.6%
The principles of the four error compensation methods are discussed, and the effectiveness of the four error compensation methods are compared through experiments. e results show that the four error compensation methods can achieve error compensation well. e compensation accuracy is consistent with the identification accuracy of the kinematic model. e pseudotarget iteration with differential form has the best performance by the comprehensive consideration of accuracy and computational efficiency
Summary
Received 15 April 2021; Revised 24 June 2021; Accepted 30 June 2021; Published 8 July 2021. E absolute positioning accuracy of industrial robots can be improved from three aspects, which are precision design, advanced control method, and error calibration. E kinematic calibration methods are mainly divided into error model-based method and axis measurement method [15, 16]. E positioning accuracy of the Staubli RX160L robot was improved from 1.41 mm to 0.15 mm based on the error model method [17]. E calibration process of the error model-based method includes four key steps, i.e., error modeling, error measurement, parameter identification, and error compensation. E position/pose error model-based calibration needs to perform the coordinate transformation. The experimental analysis on the effectiveness of kinematic error compensation methods for serial industrial robots is presented.
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