A Control Barrier Function Based Visual Servoing Framework for Safe Operation of UAVs in GNSS Denied Settings using Fiducial Markers
Unmanned Aerial Vehicles (UAVs) can offer a versatile solution for the autonomous inspection of a variety of buildings, monuments, or infrastructure. Such inspections may take place regularly or after a sudden event (e.g., earthquake) to understand the state of the point of interest and schedule preventive maintenance or capture and respond to potential damage. But UAVs are often called to operate in complex, dynamic, GNSS denied settings where the only means of navigation is by utilizing appropriate computer vision and perception schemes. In this paper, we propose a Control Barrier Function (CBF) based visual servoing framework to ensure the safe operation of a UAV in a GNSS denied setting using fiducial markers. The CBF maintains view of the marker throughout a mission, which the UAV uses to precisely localise itself in the environment. This continuous localisation ensures the UAV can control itself robustly, as well as help to accurately record information about its surroundings. The methods are experimentally validated with extensive outdoor experiments, inspecting a complex metallic structure at a public park in Auckland, New Zealand.