Optimal Recharging of Teams of Mobile Robots

In this paper, we propose an approach to extend the operational time of teams of battery-based robots by introducing a set of charging stations. We assume that the robots are heterogeneous (having different energy limits and being able to service different types of customers) and have access to a priori known map of the environment. The map is modeled as a directed, connected, and finite graph whose nodes are charging stations or customers, and arcs denote the possibility of traveling. To this end, we first formulate a task assignment and path planning problem that aims at optimizing energy consumption as well as the time needed to complete the tasks, including the time spent for recharging. Next, we propose four offline optimization techniques and one online algorithm, where the robots can dynamically adjust their paths in response to the presence of uncertainties imposed by the physical environment. Our proposed algorithms are validated through both simulation and a real-world case study on a team of unmanned aerial vehicles (UAVs) performing a joint search mission.