As urban logistics demand continues to grow, UAV delivery has become a key solution to improve delivery efficiency, reduce traffic congestion, and lower logistics costs. However, to fully leverage the potential of UAV delivery networks, efficient swarm scheduling and management are crucial. In this paper, we propose a real-time scheduling and management system based on the ``Airport-Unloading Station" model, aiming to bridge the gap between high-level scheduling algorithms and low-level execution systems. This system, acting as middleware, accurately translates the requirements from the scheduling layer into specific execution instructions, ensuring that the scheduling algorithms perform effectively in real-world environments. Additionally, we implement three collaborative scheduling schemes involving autonomous ground vehicles (AGVs), unmanned aerial vehicles (UAVs), and ground staff to further optimize overall delivery efficiency. Through extensive experiments, this study demonstrates the rationality and feasibility of the proposed management system, providing practical solution for the commercial application of UAVs delivery in urban. Code: https://github.com/chengji253/UAVDeliverySystem

翻译：随着城市物流需求持续增长，无人机配送已成为提升配送效率、缓解交通拥堵、降低物流成本的关键解决方案。然而，要充分发挥无人机配送网络的潜力，高效的集群调度与管理至关重要。本文提出一种基于“机场-卸货站”模型的实时调度与管理系统，旨在弥合高层调度算法与底层执行系统之间的鸿沟。该系统作为中间件，能够将调度层的需求精准转化为具体执行指令，确保调度算法在真实环境中有效运行。此外，我们实现了包含自主地面车辆（AGV）、无人机（UAV）与地面工作人员的三类协同调度方案，以进一步优化整体配送效率。通过大量实验，本研究验证了所提管理系统的合理性与可行性，为无人机配送在城市中的商业化应用提供了实用解决方案。代码：https://github.com/chengji253/UAVDeliverySystem