  With the introduction of new regulations in the European Union, the future of
Beyond Visual Line Of Sight (BVLOS) drones is set to bloom. This led to the
creation of the theBEAST project, which aims to create an autonomous security
drone, with focus on those regulations and on safety. This technical paper
describes the first steps of a module within this project, which revolves
around detecting obstacles so they can be avoided in a fail-safe landing. A
deep learning powered object detection method is the subject of our research,
and various experiments are held to maximize its performance, such as comparing
various data augmentation techniques or YOLOv3 and YOLOv5. According to the
results of the experiments, we conclude that although object detection is a
promising approach to resolve this problem, more volume of data is required for
potential usage in a real-life application.
