Abstract: With the rapid advancements in machine vision technology,intelligent welding techniques have witnessed increasingly widespread applications in the field of mechanical manufacturing. Three-dimensional models were constructed by using structured light cameras. An autonomous robotic welding method eliminating manual teaching procedures was developed,demonstrating automatic generation of high-precision welding paths on complex geometric profiles of cast nail rollers.Initially,the point cloud data obtained from 3D reconstruction underwent segmentation and preprocessing through algorithms such as surface fitting,pass-through filtering,region growing,and edge extraction. Subsequently,a mathematical model was established for the edge point cloud and centroid of the ceramic column to determine the welding points. Finally,the Principal Component Analysis (PCA) algorithm was employed to optimize the welding path in 3D space,enabling autonomous planning of the entire welding trajectory for the curved workpiece. Sample data indicates that the overall system error is less than 0.5 mm. Engineering test results demonstrate that the weld appearance exhibits no significant defects,fulfilling the autonomous welding production requirements for cast nail rollers through the Metal Active Gas arc welding (MAG) process. Valuable guidance and reference for the autonomous surfacing welding engineering applications of cast nail rollers with curved surfaces was provided.

Key words: autonomous welding, structured light, curved workpiece, principal component analysis algorithm, path planning