Position-Constrained Calibration Compensation for Hand–Eye Calibration in Industrial Robots

Abstract

The hand–eye calibration of laser profilers and industrial robots is a critical component of the laser vision system in welding applications. To improve calibration accuracy and efficiency, this study proposes a position-constrained calibration compensation algorithm aimed at optimizing the hand–eye transformation matrix. Initially, the laser profiler is mounted on the robot and used to scan a standard sphere from various poses to obtain the theoretical center coordinates of the sphere, which are then utilized to compute the hand–eye transformation matrix. Subsequently, the positional data of the standard sphere’s surface are collected at different poses using the welding gun tip mounted on the robot, allowing for the fitting of the sphere’s center coordinates as calibration values. Finally, by minimizing the error between the theoretical and calibrated sphere center coordinates, the optimal hand–eye transformation matrix is derived. Experimental results demonstrate that, following error compensation, the average distance error in hand–eye calibration decreased from 4.5731 mm to 0.7069 mm, indicating that the proposed calibration method is both reliable and effective.

Keywords

• line-structured light sensor
• hand-eye calibration
• welding robots
• spherical constraints