Development of a vision system integrated with industrial robots for online weld seam tracking

This paper develops a laser-structured light vision system for the industrial welding manipulator. The designed structured light vision system consisting of a line laser projector and an industrial camera is a decent 3D object data acquisition platform. By applying the principle of triangulation, the depth value of the object can be obtained via the laser plane in the captured image. According to hand-eye calibration and the principle of triangulation, the 3D position of the objects in the robot coordinate system is calculated. Based on the discriminated convolution tracker and deep reinforcement learning that increases the accuracy and processing time of the tracker, allowing simultaneous scanning for seam data acquisition and welding along the weld path, a real-time seam tracking algorithm is developed to handle the square-groove butt joint with small gaps (i.e., <1 mm). Experiments are undertaken using a Yaskawa industrial welding robot integrating the designed laser-structured light vision system. Experiment results show the significant performance of the developed system in welding square-groove butt joints with curved profiles and small gaps, i.e., the welding absolute mean error is 0.31 mm, whereas in the case of using convolution tracker only, the welding absolute mean error 1.7 mm.