A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

Abstract

A novel positioning error compensation method (PECM) based on the measured and target position error for multiple degrees of freedom (DOF) robot arm control is proposed, which is used to improve positioning accuracy of multiple-DOF robot arm end-effector in accurate positioning applications such as in the medical and mechanical fields. Based on the idea of PID to increase adaptiveness and robustness of the method, a positioning compensation model between the measured and target position error tracked by an optical tracking system and compensated joint angle is derived with inverse kinematic model. Based on error analysis of the compensation model regarding geometry errors, the proportional joint angle compensated coefficient deduced from Jaccobian matrix of the error is proposed and identified with position error data. Calibration experiments for position conversion matrix and positioning accuracy verification experiments are conducted consisting of an optical tracking system and a robot arm. The results of positioning accuracy verification experiments show that the average resultant positioning error in three directions reduces from 1.89 mm (before compensation, model based on Denavit-Hartenberg (DH)), 0.39 mm (model based on modified Denavit-Hartenberg (MDH) with Levenberg-Marquardt (LM)) to 0.34 mm (decreasing 82%, 15%), which demonstrates the efficiency and robustness of the method.

Design of closed-loop control system and key components for heavy-duty industrial robots

“…There are currently four methods for implementing closed-loop control of robots. One is a closed-loop control method based on external observation equipment to measure the pose deviation of the robot's end effector [1][2][3] . This type of method cannot measure the pose deviation of the end effector in real time and provide feedback to the robot, so it cannot make real-time correction to the pose deviation of the end effector.…”

“…However, this type of method has limited application scope and is only applicable to robots for specific purposes. The third is to construct a spatial precision grid array, so that the joint positions of the robot can be located in real-time within the grid space, thereby obtaining the real-time position of the robot's end effector [3] . This method is relatively complex and difficult to implement, and there are many practical problems that need to be solved.…”