Trajectory Design for Kinematic Constrained Cargo UAV Delivery System Based on Radio Map

This paper explores cargo delivery strategies and path planning for unmanned aerial vehicle (UAV) assigned with kinematically-constrained multi-user pickup and delivery operations. Specifically, the UAV is programmed to depart from a warehouse to complete user-generated orders and then delivery packages to designated user locations. To ensure the safety and efficiency of UAV operations, it is essential that the cargo UAV maintain a reliable connection with ground base stations (GBSs) throughout the entire flight missions. Our aim is to simultaneously enhance both the cargo delivery efficiency and energy efficiency of the system by jointly optimizing the delivery sequence and flight trajectories of the UAV. Initially, we create an urban radio map, which serves as the foundation for implementing a simulated particle swarm optimization (SPSO) algorithm. This approach efficiently determines the optimal sequence of UAV visits to the warehouse and user locations. Subsequently, using these sequences, we apply a hybrid grid search algorithm (HGSA) to meticulously plan the trajectory between pickup and delivery locations according to our objective function. Simulations comparing traditional traveling salesman problem (TSP) models and our proposed time and energy-constrained TSP with kinematic constraints (TETSPKC) show that our approach offers significant optimization advantages.