Object Detection and Motion Planning for Automated Welding of Tubular Joints
This addresses a challenging task for the marine and offshore industry, but it is incremental as it applies existing detection and planning methods to a specific domain.
The paper tackled the problem of automating welding for tubular TKY joints by developing a framework that detects joint poses using RGB-D sensors and plans collision-free trajectories with a BiTRRT algorithm, resulting in successful robot welding torch transitions to desired goals near the joint.
Automatic welding of tubular TKY joints is an important and challenging task for the marine and offshore industry. In this paper, a framework for tubular joint detection and motion planning is proposed. The pose of the real tubular joint is detected using RGB-D sensors, which is used to obtain a real-to-virtual mapping for positioning the workpiece in a virtual environment. For motion planning, a Bi-directional Transition based Rapidly exploring Random Tree (BiTRRT) algorithm is used to generate trajectories for reaching the desired goals. The complete framework is verified with experiments, and the results show that the robot welding torch is able to transit without collision to desired goals which are close to the tubular joint.