LAUSR

In this letter, we present a fast method for autonomously planing manipulation tasks for mobile manipulators. The planner defines an optimal order to perform pick-and-place operations for taking objects from a cluttered scene to specific deposit areas considering both, manipulator and mobile base motion. Our method first examines the grasping feasibility of the objects with an inverse reachability map. Then, it defines all the placing locations for the objects and analyses the corresponding preconditions to reach them. Finally, it defines a sequence for rearranging the objects that minimize the execution time. We take advantage of the environment's underlying combinatorial structure to define the shortest path. In this work, we consider both the monotone case, where each object may be moved at most once, and the non-monotone cases. An experimental evaluation on the Human Support Robot (HSR) shows the effectiveness of our solutions and the scalability of our method as the number of objects increases for both cases. Tests on monotone problem instances with 20 objects show the proposed method can save up to 17% base traveling time when comparing to baseline methods at the cost of less than 9 seconds planning time. In a test on a simple non-monotone instance, the proposed method further reduces the total execution time by 25% by minimizing the total number of actions in a few seconds of planning time. The characteristic speed in re-planning makes our method suitable for online usage.