Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles

As inspired by birds flying in flocks, their vision is one of the most critical components to enable them to respond to their neighbor’s motion. In this paper, a novel approach in developing a Vision System as the primary sensor for relative positioning in flight formation of a Leader-Follower scena...

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Main Authors: Yaghoobi, Yousef, Bahiki, Muhammad Rijaluddin, Syaril Azrad
Format: Article
Published: Blue Eyes Intelligence Engineering & Sciences Publication 2019
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author Yaghoobi, Yousef
Bahiki, Muhammad Rijaluddin
Syaril Azrad
author_facet Yaghoobi, Yousef
Bahiki, Muhammad Rijaluddin
Syaril Azrad
author_sort Yaghoobi, Yousef
collection UPM
description As inspired by birds flying in flocks, their vision is one of the most critical components to enable them to respond to their neighbor’s motion. In this paper, a novel approach in developing a Vision System as the primary sensor for relative positioning in flight formation of a Leader-Follower scenario is introduced. To use the system in real-time and on-board of the unmanned aerial vehicles (UAVs) with up to 1.5 kilograms of payload capacity, few computing platforms are reviewed and evaluated. The study shows that the NVIDIA Jetson TX1 is the most suited platform for this project. In addition, several different techniques and approaches for developing the algorithm is discussed as well. As per system requirements and conducted study, the algorithm that is developed for this Vision System is based on Tracking and On-Line Machine Learning approach. Flight test has been performed to check the accuracy and reliability of the system, and the results indicate the minimum accuracy of 83% of the vision system against ground truth data.
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institution Universiti Putra Malaysia
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spelling upm.eprints-798882023-03-23T02:10:20Z http://psasir.upm.edu.my/id/eprint/79888/ Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles Yaghoobi, Yousef Bahiki, Muhammad Rijaluddin Syaril Azrad As inspired by birds flying in flocks, their vision is one of the most critical components to enable them to respond to their neighbor’s motion. In this paper, a novel approach in developing a Vision System as the primary sensor for relative positioning in flight formation of a Leader-Follower scenario is introduced. To use the system in real-time and on-board of the unmanned aerial vehicles (UAVs) with up to 1.5 kilograms of payload capacity, few computing platforms are reviewed and evaluated. The study shows that the NVIDIA Jetson TX1 is the most suited platform for this project. In addition, several different techniques and approaches for developing the algorithm is discussed as well. As per system requirements and conducted study, the algorithm that is developed for this Vision System is based on Tracking and On-Line Machine Learning approach. Flight test has been performed to check the accuracy and reliability of the system, and the results indicate the minimum accuracy of 83% of the vision system against ground truth data. Blue Eyes Intelligence Engineering & Sciences Publication 2019 Article PeerReviewed Yaghoobi, Yousef and Bahiki, Muhammad Rijaluddin and Syaril Azrad (2019) Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles. International Journal of Innovative Technology and Exploring Engineering, 9 (2). pp. 1613-1617. ISSN 2278-3075 https://www.ijitee.org/portfolio-item/b7345129219/ 10.35940/ijitee.B7345.129219
spellingShingle Yaghoobi, Yousef
Bahiki, Muhammad Rijaluddin
Syaril Azrad
Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title_full Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title_fullStr Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title_full_unstemmed Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title_short Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
title_sort feature based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles
work_keys_str_mv AT yaghoobiyousef featurebasedstereovisionrelativepositioningstrategyforformationcontrolofunmannedaerialvehicles
AT bahikimuhammadrijaluddin featurebasedstereovisionrelativepositioningstrategyforformationcontrolofunmannedaerialvehicles
AT syarilazrad featurebasedstereovisionrelativepositioningstrategyforformationcontrolofunmannedaerialvehicles