A Vision-Based Robotic Laser Welding System for Insulated Mugs with Fuzzy Seam Tracking Control

Abstract

The symmetrical insulated mug is composed of two layers. The two ends of the two layers form the mouth and bottom seams of the insulated mug. The weld quality of the two seams is very important to keep the vacuum degree of the air between the two layers, which is vital for the heat-insulating property of the mug. Due to the narrow seam, laser welding is used. Since laser welding has high demand on the relative position of the seam and the laser torch, a vision-based seam tracking system is designed. Before welding is started, the vision sensor scans the seam and feature sample points are collected. A reconstruction algorithm is proposed to form the image containing the seam. Then, a least square fitting (LSF) method combined with random sample consensus (RANSAC) method is proposed to detect the smooth seam from the sample points. In the welding process, a seam tracking system with fuzzy logic control method is presented to keep the torch precisely on the seam. Finally, full experiments are conducted in the welding factory of the insulated mugs to verify the effectiveness of the proposed system and method.