Seam Tracking in Automated Welding

With the growing number of automated welding systems present throughout manufacturing, achieving high precision is naturally a key objective. The alignment of weld tip to weld seam, particularly in very long welds (such as in pipes), is a technical challenge in which computer vision has much to offer. This paper introduces a real-time methodology for weld-seam tracking. The key challenge associated with the weld tracking problem is to accurately locate the seam and welding tip; that is, to define image features which allow the seam and tip edges to be identified. An efficient edge detection method based on steerable filters is proposed to have a robust edge extraction in different conditions of noise and illumination. The image processing precision is experimentally verified through comparison with ground truth data.