An Efficient Recharging Task Planning Method For Multi-Robot Autonomous Recharging Problem

Abstract

As robots are increasingly employed in the warehouse operation, an important problem that needs to be solved is the Autonomous Recharging Problem (ARP); that is deciding when and where to recharge robots. Former research in ARP is disjoint that only focuses on one of above two questions, considering the high computation time. In this paper, we describe an efficient recharging task planning method to solve ARP and it includes two phases: In the first phase, recharging task planning based on task sequence segmentation is proposed for individual robot, in which both when to recharge and where to recharge are considered to maximize operational efficiency. And it also improves the computation efficiency by segmenting task sequence and planning each recharging task recursively. In the second phase, all robots task sequences with planned recharging tasks are centralized and selected recharging stations of some planned recharging tasks are reallocated, using maximum bipartite graph matching to reduce waiting time for other robots recharging and improve overall task execution efficiency. The proposed method is validated by means of simulation in a real warehouse environment.