The anticipated widespread use of unmanned aerial vehicles (UAVs) raises significant safety and security concerns, including trespassing in restricted areas, colliding with other UAVs, and disrupting high-traffic airspaces. To mitigate these risks, geofences have been proposed as one line of defence, which limit UAVs from flying into the perimeters of other UAVs and restricted locations. In this paper, we address the concern that existing geometric geofencing algorithms lack accuracy during the calculation of complex geofences, particularly in dynamic urban environments. We propose a new algorithm based on alpha shapes and Voronoi diagrams, which we integrate into an on-drone framework using an open-source mapping database from OpenStreetMap. To demonstrate its efficacy, we present performance results using Microsoft's AirSim and a low-cost commercial UAV platform in a real-world urban environment.
翻译:预计大规模使用无人驾驶飞行器(无人驾驶飞行器)将引起严重的安全和安保关切,包括侵入禁区、与其他无人驾驶飞行器发生碰撞以及破坏高流量空域。为减轻这些风险,建议将地理栅栏作为防线,限制无人驾驶飞行器飞入其他无人驾驶飞行器和受限制地点的周界。在本文件中,我们讨论了以下关切:在计算复杂的地理栅栏时,特别是在动态城市环境中,现有的几何几何几何定位算法缺乏准确性。我们提出了以字母形状和沃罗诺伊图为基础的新算法,我们利用OpenStreetMap的开放源地图数据库将其纳入一个在轨框架。为了展示其功效,我们利用微软的AirSim和一个在现实世界城市环境中的低成本商业无人驾驶飞行器平台展示了绩效结果。