High-efficiency automated triaxial robot grasping system for motor rotors using 3D structured light sensor

With the rapid development of artificial intelligence and computer vision, numerous technologies have been introduced to automate manufacturing in the industry. Typical metal workpieces in the industry often have highly reflective surfaces, come in various sizes, and are positioned irregularly. The motor rotor presented in this paper is one such representative workpiece. Traditional grasping methods for workpiece loading and unloading are pre-programmed and often struggle to cope with complex and disordered situations. In this paper, we introduce a structured light (SL) sensor as the visual guide for the triaxial robot. Furthermore, we propose a high-precision hand-eye calibration method for the non-orthogonal coordinate system of the triaxial robot. Additionally, a motor rotor center localization method based on U-Net image segmentation is proposed. By combining the high-precision hand-eye calibration and localization, we can accurately and automatically locate and grasp the rotor. We have conducted sufficient experiments to verify the effectiveness and accuracy of our system.