共享动态空域中多无人机预飞行规划
Multi UAVs Preflight Planning in a Shared and Dynamic Airspace
AI总结：
DTAPP-IICR通过增量迭代冲突解决方法，实现了在动态共享空域中大规模无人机预飞行规划的高效与高成功率。
摘要：
大规模无人机（UAV）编队在动态共享空域中的预飞行规划面临重大挑战，包括时间禁飞区（NFZ）、异构车辆特性以及严格的时间交付截止要求。虽然多智能体路径寻找（MAPF）提供了一个形式化框架，但现有方法往往缺乏实际无人机交通管理（UTM）所需的可扩展性和灵活性。我们提出DTAPP-IICR：一种基于交付时间的优先规划方法，结合增量和迭代冲突解决。我们的框架首先通过优先考虑紧急任务生成初始解决方案。其次，使用SFIPP-ST，一种新的四维单智能体规划器（安全飞行间隔路径规划，带有软和时间约束），计算往返路径。SFIPP-ST处理异构无人机，严格执行时间NFZ，并将智能体间的冲突建模为软约束。随后，通过几何冲突图引导的迭代大邻域搜索，高效解决任何残留冲突。一种保持完整性的方向剪枝技术进一步加速了三维搜索。在具有时间NFZ的基准测试中，DTAPP-IICR在多达1000架无人机的编队中实现了近100%的成功率，并通过剪枝获得了高达50%的运行时间减少，优于批量增强冲突基于搜索在UTM环境中的表现。在现实城市规模操作中成功扩展，其中其他基于优先级的方法在中等部署中也失败，DTAPP-IICR被定位为一种实用且可扩展的解决方案，用于密集动态城市空域的预飞行规划。
英文摘要：
Preflight planning for large-scale Unmanned Aerial Vehicle (UAV) fleets in dynamic, shared airspace presents significant challenges, including temporal No-Fly Zones (NFZs), heterogeneous vehicle profiles, and strict delivery deadlines. While Multi-Agent Path Finding (MAPF) provides a formal framework, existing methods often lack the scalability and flexibility required for real-world Unmanned Traffic Management (UTM). We propose DTAPP-IICR: a Delivery-Time Aware Prioritized Planning method with Incremental and Iterative Conflict Resolution. Our framework first generates an initial solution by prioritizing missions based on urgency. Secondly, it computes roundtrip trajectories using SFIPP-ST, a novel 4D single-agent planner (Safe Flight Interval Path Planning with Soft and Temporal Constraints). SFIPP-ST handles heterogeneous UAVs, strictly enforces temporal NFZs, and models inter-agent conflicts as soft constraints. Subsequently, an iterative Large Neighborhood Search, guided by a geometric conflict graph, efficiently resolves any residual conflicts. A completeness-preserving directional pruning technique further accelerates the 3D search. On benchmarks with temporal NFZs, DTAPP-IICR achieves near-100% success with fleets of up to 1,000 UAVs and gains up to 50% runtime reduction from pruning, outperforming batch Enhanced Conflict-Based Search in the UTM context. Scaling successfully in realistic city-scale operations where other priority-based methods fail even at moderate deployments, DTAPP-IICR is positioned as a practical and scalable solution for preflight planning in dense, dynamic urban airspace.
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