Motivated by the increased use of UAS in commercial applications, in this paper we tackle the problem of path planning when requests are submitted by UAS managed by different operators. We propose the new problem of generalized path planning for UAS Traffic Management, where the UAS path is described by operators with a sequence of waypoint groups and a solution trajectory must pass through a waypoint in each group. This problem is typical for applications where multiple charging stations and pickup/drop-off locations are distributed in a flight area. Our solution builds upon prior work on discretized space-time graph path planning and proposes a novel multi-source/multi-destination graph search algorithm that generates collision-free trajectories for pre-flight CDR. Our efficient algorithm has runtime proportional to the number of groups and avoids combinatorial explosion. We apply our mechanism to the energy-constrained UAS package delivery problem with multiple warehouses and battery charging stations. Simulation results show that our algorithm is efficient and scalable with the number of requests and graph size. The addition of charging stations and the option for multiple warehouses increases the request admission ratio and reduces the overall trajectory duration, effectively improving both the planner’s quality of service and the efficiency of airspace usage.

中文翻译：

---

具有时空图的 UTM 系统的广义路径规划


由于无人机在商业应用中的使用不断增加，在本文中，我们解决了由不同运营商管理的无人机提交请求时的路径规划问题。我们提出了 UAS 交通管理的广义路径规划的新问题，其中 UAS 路径由操作员用一系列航路点组来描述，并且解决方案轨迹必须经过每个组中的一个航路点。对于飞行区域内分布有多个充电站和接送地点的应用来说，这个问题很常见。我们的解决方案建立在离散时空图路径规划的先前工作的基础上，并提出了一种新颖的多源/多目的地图搜索算法，该算法可为飞行前 CDR 生成无碰撞轨迹。我们高效的算法的运行时间与组的数量成正比，并避免组合爆炸。我们将我们的机制应用于具有多个仓库和电池充电站的能源受限的无人机包裹递送问题。模拟结果表明，我们的算法是高效的，并且可以根据请求数量和图大小进行扩展。充电站的增加和多个仓库的选择提高了请求准入率并减少了整体轨迹持续时间，有效提高了规划人员的服务质量和空域使用效率。