Vision-based runway detection and landing for unmanned aerial vehicle enhanced autonomy

Tsapparellas, K., Jelev, N., Waters, J. et al. (2 more authors) (2023) Vision-based runway detection and landing for unmanned aerial vehicle enhanced autonomy. In: 2023 IEEE International Conference on Mechatronics and Automation (ICMA) Proceedings. 2023 IEEE International Conference on Mechatronics and Automation (ICMA), 06-09 Aug 2023, Harbin, Heilongjiang, China. Institute of Electrical and Electronics Engineers (IEEE) , pp. 239-246. ISBN 9798350320855

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Item Type: Proceedings Paper
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© 2023 The Authors. Except as otherwise noted, this author-accepted version of a paper published in 2023 IEEE International Conference on Mechatronics and Automation (ICMA) Proceedings is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Keywords: Unmanned Aerial Vehicles (UAVs); Autonomous Landing; Runway Detection; Autonomy; X-Plane 11 flight simulator; Computer Vision; Vision-based landing
Dates:
  • Published: 22 August 2023
  • Published (online): 22 August 2023
  • Accepted: 15 May 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
Funder
Grant number
INNOVATE UK
10023377 TS/W02005X/1
Depositing User: Symplectic Sheffield
Date Deposited: 14 Jun 2023 14:04
Last Modified: 05 Mar 2025 16:51
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/ICMA57826.2023.10215523
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