Multi-Auctioneer Market-based Task Scheduling for Persistent Drone Delivery

Abstract

Market-based task allocation methods represent an effective strategy for scheduling heterogeneous tasks to a heterogeneous multi-agent system, e.g., a fleet of different Unmanned Aerial Vehicles (UAVs). This is mainly due to their computational efficiency, ease of hybridization with optimization techniques and adaptability to different communication architectures. In this paper, a novel hybrid auction-based task allocation architecture with multi-auctioneer agents’ behavior is proposed for an Urban Air Mobility application. The proposed method aims to solve the combined problem of: (i) scheduling parcel pick-up and delivery tasks with time deadlines while minimizing the drones’ energy consumption; (ii) scheduling battery re-charge tasks in order to ensure the service’s persistency; and (iii) evaluating safe aerial routes since the UAVs fly over populated areas. The validity of the approach is demonstrated through Monte Carlo simulations. Moreover, being the proposed architecture distributed among the UAVs, the impact of communication failures on well-defined solution quality parameters is also investigated.