Optimization Framework for Global Path Planning and Local Motion Planning for Robotic Welding of Multiple Large Industrial Parts

To automate the welding of multiple industrial parts that are too large for conveyor belts, we designed a mobile manipulator to perform welding around large parts and move between them. In our previous paper, we devised a motion planner to optimize the mobile welding motion. In this paper, we complete the automation by proposing a framework to optimize the path traveled between these large parts and the welding paths around each part. We model it as a Traveling Salesman Problem with Neighborhoods (TSPN), where the neighborhoods represent the parts, and the points in the neighborhoods represent the robot's welding positions around the parts. As opposed to previous TSPN solvers, our method optimizes the total path, which is the sum of both paths between neighborhoods (global path) and inside each neighborhood (local path). Also, entry and exit points for each neighborhood are defined to remove unnecessary traveling back to the entry point. In a simulation test case, our method resulted in path length reduction of 13.2% compared to the method with same entry and exit and without considering the welding paths. The scalability of this method was tested by adding more parts, which resulted in a higher path length reduction of 17%. Complexity was also increased by adding obstacles, which resulted in an even higher path length reduction of 25.5%. In our ship hull parts welding simulation, we show that our method is able to calculate an optimized path that visits all parts and the welding points around the parts. It shows that with our approach, the automation of large part welding is feasible as well as optimized.