Landing Area Recognition using Deep Learning for Unammaned Aerial Vehicles

Abstract

The lack of an automated Unmanned Aerial Vehicles (UAV) landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace to develop tasks in the logistical transport scenario. This research proposes landing area localization and obstruction detection for UAVs that are based on deep learning faster R-CNN and feature matching algorithm. Which output decides if the landing area is safe or not. The final result has been deployed on the Aerial Mobile Robot Platform and was successfully performed effectively.