Structured Light-Based Visual Servoing for Robotic Pipe Welding Pose Optimization

摘要

In order to optimize the pose of welding torch preplanned by offline programming, a structured light-based visual servoing method is proposed. First of all, a series of phase shifting patterns are projected to acquire the so-called phase map. Afterwards, unlike usual feature extraction methods, which were based on 3-D cloud, a cylinder axis is extracted directly from the phase map to represent the connecting pipes' cylindrical surface. Then, a visual servoing control law based on the axis combined with the seam center in phase map is proposed to optimize the pose of the welding torch. Moreover, global asymptotic stability of this method is proved. Finally, simulations and real experiments are performed to demonstrate the effectiveness and robustness of this method. Results show this method can improve the mean error of deviated distance and angle of offline programming by 73.5% and 82.5%, respectively.