UAV Emergency Landing Site Selection System using Machine Vision

Faheem Muhammad Rao, Sumair Aziz, Adnan Khalid, Mudassar Bashir, Amanullah Yasin


This paper address the problem area of Unmanned Aerial Vehicles (UAV) emergency scenarios in which forced or emergency landing becomes imperative. Emergency or forced landing becomes crucial when there is system failure which impacts the flight safety and UAV is unable to fly back to the emergency landing runway. This failure could be due to data link loses, GPS failure, engine or flight surface failure. Forced landing needs to be performed on safe landing site which could be plane surface, open fields or grounds. First step to accomplish the successful forced landing safely is to search and select the safe landing site. This article presents the system design which assists the UAV in selection of safe landing site having no obstacles, buildings and trees. The proposed system design uses computer vision and machine learning techniques in order to classify feasible and non-feasible landing sites. The proposed algorithms in this article also incorporate the scenarios having low lighting conditions due to clouds. The system has been designed and simulated in MATLAB and promising results have been achieved with very less processing time and computational power.


UAV; Forced landing; Emergency Landing; Machine Vision; Machine Learning; UAV GPS Failure; K-Nearest Neighbor.

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ISSN: 2377-2220   

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