Welding Line Detection Using Point Clouds from Optimal Shooting Position

A method for welding line detection using point cloud data is proposed to automate welding operations com-bined with a contact sensor. The proposed system tar-gets a fillet weld, in which the joint line between two metal plates attached vertically is welded. In the pro-posed method, after detecting the position and orienta-tion of two flat plates regarding a single viewpoint as a rough measurement, the flat plates are measured from the optimal shooting position in each plane in detail to detect a precise weld line. When measuring a flat plate from an angle, the 3D point cloud obtained by a depth camera contains measurement errors. For example, a point cloud measuring a plane has a wavy shape or void owing to light reflection. However, by shooting the plane vertically, the point cloud has fewer errors. Using these characteristics, a two-step measurement algorithm for determining weld lines was proposed. The weld line detection results show an improvement of 5 mm compared with the rough and precise mea-surements. Furthermore, the average measurement error was less than 2.5 mm, and it is possible to nar-row the range of the search object contact sensor for welding automation.