Runway detection for UAV landing system

Antal Hiba, Tamas Zsedrovits, Orsolya Heri, Akos Zarandy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationCNNA 2018 - 16th International Workshop on Cellular Nanoscale Networks and Their Applications
EditorsAkos Zarandy
PublisherIEEE Computer Society
Pages86-89
Number of pages4
ISBN (Electronic)9783800747665
Publication statusPublished - Jan 1 2018
Event16th International Workshop on Cellular Nanoscale Networks and Their Applications, CNNA 2018 - Budapest, Hungary
Duration: Aug 28 2018Aug 30 2018

Publication series

NameInternational Workshop on Cellular Nanoscale Networks and their Applications
Volume2018-August
ISSN (Print)2165-0160
ISSN (Electronic)2165-0179

Conference

Conference16th International Workshop on Cellular Nanoscale Networks and Their Applications, CNNA 2018
CountryHungary
CityBudapest
Period8/28/188/30/18

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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  • Cite this

    Hiba, A., Zsedrovits, T., Heri, O., & Zarandy, A. (2018). Runway detection for UAV landing system. In A. Zarandy (Ed.), CNNA 2018 - 16th International Workshop on Cellular Nanoscale Networks and Their Applications (pp. 86-89). (International Workshop on Cellular Nanoscale Networks and their Applications; Vol. 2018-August). IEEE Computer Society.