부산대학교 도서관

In order to achieve intelligent and flexible welding, complete the extraction and path planning of 3-D complex weld seam of large steel weldment, and solve the problems that in the vision-guided welding process, the scanning path depends on manual teaching, and the offline programming depends on the machining and assembly accuracy of the weldment; a vision-guided method for welding robots based on a line structured-light sensor is proposed. First, the 3-D computer aided design (CAD) model of the weldment is used to build an offline welding knowledge library, and then, the scanning path is planned in combination with the point cloud alignment. Then, the sensor collects the point cloud on the surface of the weldment along the scanning path. Second, different weld seam extraction algorithms are proposed according to different weld types. The random sample consensus (RANSAC) algorithm is used to identify the position of weld feature points, and the three-frame method is used to solve the pose of weld feature points. Finally, the weld seam is generated to guide the welding robot to complete the welding operation. The experimental results show that the proposed method can be used for different types and dimensions of weldments and provides flexible welding operations with better versatility and higher intelligence.