relation: https://khub.utp.edu.my/scholars/20243/
title: Integrating Computer Vision and Photogrammetry for Autonomous Aerial Vehicle Landing in Static Environment
creator: Subramanian, J.A.
creator: Asirvadam, V.S.
creator: Zulkifli, S.A.B.M.
creator: Singh, N.S.S.
creator: Shanthi, N.
creator: Lagisetty, R.K.
creator: Kadir, K.A.
description: In recent years, the research has focused firmly on Autonomous Aerial Vehicles (AAVs) owing to their vast array of potential applications, to aid those applications this study presents a technical approach for source localization and landing trajectory identification for Autonomous Aerial Vehicle (AAV) landing, leveraging computer vision and photogrammetry techniques. The proposed method aims to achieve accurate and robust localization of the landing target area and precise determination of the AAV's landing trajectory. The source localization module utilizes a computer vision system equipped with onboard cameras and advanced image processing algorithms. The system captures images of the target area and performs feature extraction and matching to estimate the position of the landing target. Additionally, the A� algorithm serves as a pivotal tool in deriving an optimized trajectory by harnessing the relative positions of the Autonomous Aerial Vehicle (AAV) and the designated landing target. © 2013 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2024
type: Article
type: PeerReviewed
identifier:   Subramanian, J.A. and Asirvadam, V.S. and Zulkifli, S.A.B.M. and Singh, N.S.S. and Shanthi, N. and Lagisetty, R.K. and Kadir, K.A.  (2024) Integrating Computer Vision and Photogrammetry for Autonomous Aerial Vehicle Landing in Static Environment.  IEEE Access, 12.  pp. 4532-4543.  ISSN 21693536     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85181557999&doi=10.1109%2fACCESS.2024.3349419&partnerID=40&md5=f79b033bdd0369a9693ecf3496a07e3b
relation: 10.1109/ACCESS.2024.3349419
identifier: 10.1109/ACCESS.2024.3349419