提出一种高效调度算法，让上千架无人机快速安全地完成编队初始排列。
A Time-efficient Prioritised Scheduling Algorithm to Optimise Initial Flock Formation of Drones
- 按碰撞风险和路径阻碍度为无人机排序，动态分配延迟避免冲突
- 可实现5000架无人机的无碰撞编队，比现有方法更快更省计算资源
- 适合大规模无人机协同任务，如灾后搜救、空中物流
无人机应用持续扩展，群体飞行虽提升协作能力，但初始编队阶段面临效率与可扩展性挑战。现有算法在潜在碰撞导致无人机进入次优轨迹时表现不佳。本文提出一种时间高效的优先级调度算法，优化无人机群初始编队过程。该方法根据每架无人机的潜在碰撞数及其对其他无人机造成永久阻挡的可能性，为其分配优先级。基于此优先级层次，每架无人机计算合适延迟以确保无碰撞路径。仿真结果表明，该算法可成功生成最多5000架无人机的无碰撞轨迹，并在性能和计算效率上优于基于耦合度的启发式优先规划方法（CDH-PP）。
原文摘要 · Abstract (English)
Drone applications continue to expand across various domains, with flocking offering enhanced cooperative capabilities but introducing significant challenges during initial formation. Existing flocking algorithms often struggle with efficiency and scalability, particularly when potential collisions force drones into suboptimal trajectories. This paper presents a time-efficient prioritised scheduling algorithm that improves the initial formation process of drone flocks. The method assigns each drone a priority based on its number of potential collisions and its likelihood of reaching its target position without permanently obstructing other drones. Using this hierarchy, each drone computes an appropriate delay to ensure a collision-free path. Simulation results show that the proposed algorithm successfully generates collision-free trajectories for flocks of up to 5000 drones and outperforms the coupling-degree-based heuristic prioritised planning method (CDH-PP) in both performance and computational efficiency.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。