Runway detection for UAV landing system
Konferenz: CNNA 2018 - The 16th International Workshop on Cellular Nanoscale Networks and their Applications
28.08.2018 - 30.08.2018 in Budapest, Hungary
Tagungsband: CNNA 2018
Seiten: 4Sprache: EnglischTyp: PDF
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Autoren:
Hiba, Antal; Zarandy, Akos (Computational Optical Sensing and Processing Laboratory, Institute for Computer Science and Control, Hungarian Academy of Sciences, Hungary & Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Hungary)
Zsedrovits, Tamas (Faculty of Information Technology and Bionics, Peter Pazmany Catholic University, Hungary)
Heri, Orsolya (Computational Optical Sensing and Processing Laboratory, Institute for Computer Science and Control, Hungarian Academy of Sciences, Hungary)
Inhalt:
Vision-based UAV (Unmanned Aerial Vehicle) landing on runways is an emerging topic, because of the possible wide range of applications. Vision-based landing technology can also give an additional independent source of information for civil aviation landing systems. The core of the problem is the detection of the runway and other possible features. This paper introduces a simple framework for runway detection, in the case when only the threshold marker is painted. The approach utilizes corner features and convolutional neural nets for ROI classification.