On Integrated Optimal Task and Motion Planning for a Tractor-Trailer Rearrangement Problem

In this work, a combined task and motion planner for a tractor and a set of trailers is proposed and it is shown that it is resolution complete and resolution optimal. The proposed planner consists of a task planner and a motion planner that are both based on heuristically guided graph-search. As a step towards tighter integration of task and motion planning, we use the same heuristic that is used by the motion planner in the task planner as well. We further propose to use the motion planner heuristic to give an initial underestimate of the motion costs that are used as costs during the task planning search, and increase this estimate gradually by using the motion planner to verify the cost and feasibility of actions along paths of interest. To limit the time spent in the motion planner, the use of time and cost limits to pause or prematurely abort the motion planner is proposed, which does not affect the resolution completeness or resolution optimality. The planner is evaluated on numerical examples and the results show that the proposed planner can significantly reduce the execution time compared to a baseline resolution optimal task and motion planner.