An automatic seam extraction method based on improved DLP structured light vision inrobotic welding

Purpose Due to the increasing automation requirements for robotic welding, automatic seam extraction has become a research hotspot. The welding objects in this paper are a type of multi-variety gate-shaped workpieces, the shapes of workpieces and the distribution of seams are uncertain, the current seam extraction methods are difficult to deal with. For this challenge, this paper aims to propose an automatic seam extraction method based on the improved DLP vision system. Design/methodology/approach In this paper, an improved DLP (Digital Light Processing) structured light vision system is first set up, which integrates 2D seam region detection results into the 3D point cloud reconstruction process. By this solution, several independent point clouds of different seam regions can be generated, and the type of seam on each point cloud can also be obtained. Subsequently, for different types of welding seams, the corresponding seam extraction algorithms are designed by analyzing the local structural characteristics. Findings The experimental results demonstrate the proposed improved DLP structured light vision system can automatically, accurately and efficiently complete the seam extraction for the workpieces with multiple seams of different types in the field of view. Originality/value The proposed method enhances robotic welding automation for workpieces with multiple seams of different types, overcoming the limitations of the current methods.