A Novel Multi-Layer Framework for BVLoS Drone Operation: A Preliminary Study

TL;DR

This paper introduces a multi-layer framework for planning beyond visual line of sight (BVLoS) drone operations using ground cellular networks, focusing on safety, infrastructure, and obstacles, solved via a graph-based approach.

Contribution

It proposes a novel multi-layer framework for BVLoS drone planning that incorporates real-world constraints and uses a graph algorithm for mission planning.

Findings

Framework effectively models real-world BVLoS challenges.

Graph-based planning ensures dependability in drone missions.

Preliminary results demonstrate feasibility of the approach.

Abstract

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.