Unmanned Aircraft Systems (UAS) provide the platform of many applications such as efficient package delivery, monitoring, surveillance, search and rescue, and more. As the density of UAS deployed in urban areas for delivery and monitoring operations is expected to increase in the near future, it becomes critical to design an efficient collision-free UAS path planning system to be used by a centralized traffic manager. In this article we propose an on-demand, scalable, collision-free trajectory planning mechanism that processes routing requests in batches, with the objective of improving the ratio of successfully admitted requests. The planner transforms the input map to a unit graph discretized on the safety distance and computes trajectories using search in the derived space-time graph. The planner generates trajectories that are by design conflict-free and deadlock-free. The performance of our algorithm is analyzed with simulations. We measure admission ratio, the delay overhead vs. optimal path delay, the algorithm running time, and we compare results with prior work. The proposed batch planner yields better admission ratio and delay overhead in low and medium density scenarios. In all scenarios it has a running time that is 4-7 times shorter, showing its scalability in practical situations.

中文翻译：

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具有时空图的UAS批生产路径规划

无人机系统（UAS）提供了许多应用程序的平台，例如高效的包裹递送，监视，监视，搜索和救援等。由于预计在不久的将来部署在市区中用于交付和监视操作的UAS的密度将会增加，因此设计一个有效的无碰撞UAS路径规划系统以供集中交通管理人员使用变得至关重要。在本文中，我们提出了一种按需，可伸缩，无冲突的轨迹计划机制，该机制可以批量处理路由请求，目的是提高成功接受请求的比例。计划者将输入地图转换为在安全距离上离散的单位图，并使用在导出的时空图中进行搜索来计算轨迹。规划器生成的轨迹在设计上没有冲突且没有死锁。通过仿真分析了我们算法的性能。我们测量准入率，延迟开销与最佳路径延迟，算法运行时间，并将结果与​​先前的工作进行比较。拟议的批处理计划程序在中低密度方案中产生更好的准入率和延迟开销。在所有情况下，它的运行时间都缩短了4-7倍，显示了在实际情况下的可伸缩性。