Abstract
Based on the current situation of high precision and comparatively low APA (absolute positioning accuracy) in industrial robots, a calibration method to enhance the APA of industrial robots is proposed. In view of the "hidden" characteristics of the RBCS (robot base coordinate system) and the FCS (flange coordinate system) in the measurement process, a comparatively general measurement and calibration method of the RBCS and the FCS is proposed, and the source of the robot terminal position error is classified into three aspects: positioning error of industrial RBCS, kinematics parameter error of manipulator, and positioning error of industrial robot end FCS. The robot position error model is established, and the relation equation of the robot end position error and the industrial robot model parameter error is deduced. By solving the equation, the parameter error identification and the supplementary results are obtained, and the method of compensating the error by using the robot joint angle is realized. The Leica laser tracker is used to verify the calibration method on ABB IRB120 industrial robot. The experimental results show that the calibration method can effectively enhance the APA of the robot.
Highlights
With the wide application of industrial robot, people have higher requirements for its positioning accuracy
The positioning accuracy of industrial robots can be divided into two parts: repeated positioning accuracy and absolute positioning accuracy (APA) [1]
This paper aims to enhance the APA
Summary
With the wide application of industrial robot, people have higher requirements for its positioning accuracy. It is important to study the positioning accuracy improvement method of industrial robot. We only need to improve the repeated positioning accuracy of the robot. When industrial robot welds a workpiece, the repeated accuracy of the robot normally determines the trajectory accuracy of the workpiece directly. At this time, the APA is meaningless. People focus on how to improve the repeat positioning accuracy, which can be improved by many methods such as soft computing and machine learning [2,3]
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