Multi-robot path planning for smart access of distributed charging points in map

Abstract

Autonomous mobile robots are being used to automate many tasks such as cleaning, delivering items, and surveillance. Such tasks often require uninterrupted and continuous service. However, robots have limited battery power and must be recharged frequently. Since manually charging each robot is not always feasible, automatic charging (docking) stations have been developed to automate the process of charging. In a multi-robot system, the tasks are generally distributed between the robots, and different robots have different amounts of remaining battery power. Since the charging stations are expensive, a limited number of charging points are generally available. Hence, an intelligent planner to manage a limited number of charging points for a large number of robots is essential. In this work, we propose a multi-robot path planner for intelligently accessing a limited number of charging points distributed on the map. Unlike traditional path planners, which mainly consider the shortest path criterion to generate paths, the proposed planner also considers the remaining battery power of the robots, task priority, and robot’s location in the map. It allocates the most appropriate charging station to the robots, which require recharging. Simulation results show that the proposed planner can reduce trajectory re-planning, and plan efficient paths to the available charging points.