On optimizing a sequence of robotic tasks

Production speed and energy efficiency are crucial factors for any application scenario in industrial robotics. The most important factor for this is planning of an optimized sequence of atomic subtasks. In a welding scenario, an atomic subtask could be understood as a single welding seam/spot while the sequence could be the ordering of these atomic tasks. Optimization of a task sequence is normally modeled as the Traveling Salesman Problem (TSP). This works well for simple scenarios with atomic tasks without execution freedom like spot welding. However, many types of tasks allow a certain freedom of execution. A simple example is seam welding of a closed-contour, where typically the starting-ending point is not specified by the application. This extra degree of freedom allows for much more efficient task sequencing. In this paper, we describe an extension of TSP to model a problem of finding an optimal sequence of tasks with such extra degree of freedom. We propose a new, efficient heuristic to solve such problems and show its applicability. Obtained computational results are close to the optimum on small instances and outperforms the state of the art approaches on benchmarks available in literature.