Drones have become increasingly popular in a variety of fields, including agriculture, emergency response, and package delivery. However, most drone operations are currently limited to within Visual Line of Sight (vlos) due to safety concerns. Flying drones Beyond Visual Line of Sight (bvlos) presents new challenges and opportunities, but also requires new technologies and regulatory frameworks, not yet implemented, to ensure that the drone is constantly under the control of a remote operator. In this preliminary study, we assume to remotely control the drone using the available ground cellular network infrastructure. We propose to plan bvlos drone operations using a novel multi-layer framework that includes many layers of constraints that closely resemble real-world scenarios and challenges. These layers include information such as the potential ground risk in the event of a drone failure, the available ground cellular network infrastructure, and the presence of ground obstacles. From the multi-layer framework, a graph is constructed whose edges are weighted with a dependability score that takes into account the information of the multi-layer framework. Then, the planning of bvlos drone missions is equivalent to solving the Maximum Path Dependability Problem on the constructed graph, which turns out to be solvable by applying Dijkstra's algorithm.
翻译:无人驾驶飞机的飞行无人机在视觉视线之外(bvlos)带来了新的挑战和机遇,但也需要尚未实施的新技术和监管框架,以确保无人驾驶飞机始终处于远程操作者的控制之下。在这项初步研究中,我们假定利用现有的地面移动电话网络基础设施遥控控制无人驾驶飞机。我们提议使用一个新的多层框架规划无人驾驶飞机作业,其中包括许多与现实世界情景和挑战密切相关的制约层。这些层面包括无人机失灵情况下潜在的地面风险、现有的地面移动电话网络基础设施以及地面障碍等信息。从多层框架来看,图的边缘是加权的,其可靠性分数考虑到多层框架的信息。然后,Bvlos无人驾驶飞机飞行任务的规划等同于解决构建图上的最大路径可依赖性问题,该图将转换为可应用的软件算算法。