Research on the Accuracy of Robot End Position Based on Joint Motion Error

In robotic intelligent manufacturing engineering, the machining accuracy of workpieces is directly related to the end positioning accuracy of six-degree-of-freedom serial robots, so compensating for the latter is of great significance. This article proposes a method to improve the absolute positioning accuracy of a robot by correcting the joint angles of the robot without changing the parameters of the robot controller. Firstly, establish a forward kinematics model of the robot based on the spiral theory. Then, the motion errors of each joint of the robot are measured using a laser tracker, and the RBF neural network is trained to predict the motion errors of each joint of the robot. Finally, the predicted joint motion errors are compensated for the theoretical joint angles, thereby improving the accuracy of robot end positioning. The experimental results show that the precision of the robot’s end position has been improved from 0.2456 mm to 0.0716 mm, verifying the effectiveness of this method.