2021/10/18 by Vihangi Vagal, Konstantinos Markantonakis, Vagal, Vihangi +3
Computer Science · Earth and Planetary Sciences · Engineering · Environmental Science · #3D Surveying and Cultural Heritage #Computational Geometry (cs.CG) #FOS: Computer and information sciences #Remote Sensing and LiDAR Applications #Robotics (cs.RO) #Robotics and Sensor-Based Localization #cs.CG #cs.RO
paper · pdf · doi:10.48550/arxiv.2110.09453
Accepted to the 40th IEEE Digital Avionics Systems Conference
arxiv created 2021/10/18 · openalex publication_date 2021/10/18 · arxiv updated 2021/10/19 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
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.