Online Scheduling for Aerial Recovery of Multiple UAVs

Abstract

This paper studies online scheduling for recovering unmanned aerial vehicles (UAVs) in the air. We propose a genetic algorithm (GA) to obtain the schedule for recovering multiple UAVs. In real-world environment, the optimal recovery sequence needs to be regenerated when some UAVs leave the recovery sequence due to emergency or new UAVs arrive and join for recovery. An elite seeding strategy is developed and then integrated into the GA to update the recovery sequence. The simulation results show that the GA with elite seeding strategy can quicken the iteration process of finding the best recovery sequence in dynamic scenarios.