Energy Minimization for Radio Map-Based UAV Pickup and Delivery Logistics System

Cargo UAVs have been used in short-distance logistics scenarios in cities, and this paper investigates the path planning problem for multi-user pickup and delivery of UAVs. The UAV takes off from the depot, completes the pickup and delivery tasks, and returns to the depot; it needs to maintain a reliable connection with the ground base station (GBS) during the UAV's flight. In the mission, the energy consumption of the UAV is closely related to the order of pickup and delivery as well as the weight of the goods. Therefore, this paper achieves the goal of minimizing UAV energy consumption and designing UAV flight trajectory by optimizing the access sequence. In this paper, we first construct a radio map of the target area, and then we propose an improved Dijkstra's algorithm to calculate the path which is the shortest between any two access points that satisfies reliable communication. Then, using the constructed distance matrix, we use a hybrid genetic algorithm (HGA) to solve the UAV trajectory of the minimum energy pickup and delivery problem (PDP). Finally, through the simulation analysis of traditional PDP and energy-efficient PDP on the python platform, it can be found that our proposed minimum energy consumption PDP saves about 20% of energy consumption compared with the traditional PDP without considering energy consumption.