  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.
