A Real-Time System for Scheduling and Managing UAV Delivery in Urban Areas
This addresses the need for practical, real-time management systems to enable commercial UAV delivery in urban logistics, though it appears incremental as it builds on existing scheduling algorithms with middleware integration.
The paper tackles the problem of efficient swarm scheduling and management for UAV delivery in urban areas by proposing a real-time system based on an 'Airport-Unloading Station' model, which acts as middleware to translate scheduling algorithms into execution instructions and includes collaborative schemes with AGVs and ground staff, demonstrating rationality and feasibility through experiments.
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