Energy Consumption Optimization for Cellular-Connected Multi-UAV Pickup and Delivery System

In this paper, a cellular-connected uncrewed aerial vehicles (UAVs) pickup and delivery system is studied in which the multiple UAVs are served by ground base station (GBS). These UAVs commence operations from the hangar, systematically execute a sequence of pickups and deliveries before returning, all while maintaining a continuous and reliable communication link with the GBS throughout their missions. Owing to the limited onboard energy resources of UAVs and the influence of task sequence and payload characteristics on UAV’s energy consumption, this study focuses on minimizing energy usage through the optimization of task sequences and flight trajectories. Firstly, a radio map of the operational area is constructed to identify flight zones that ensure reliable communication, an improved Dijkstra algorithm is then proposed to compute the shortest viable path between any two access points that satisfy reliable communication criteria. Furthermore, a chromosome structure tailored for a hybrid genetic algorithm (HGA) is devised to address the complexities of multi-UAV task allocation. With the aid of a developed distance matrix, the HGA is utilized to determine the optimal delivery sequence, thereby achieving the objectives of minimizing the maximum energy consumption (MME) and minimizing the sum energy consumption (MSE) respectively. Finally, simulation analyses demonstrate that the proposed MME and MSE optimization strategies enable approximately a 50% reduction in peak flight energy consumption and around a 40% decrease in total energy consumption, compared to multi-UAV pickup and delivery systems without energy optimization.