The University of Southampton
University of Southampton Institutional Repository

An underwater visual navigation method based on multiple ArUco markers

An underwater visual navigation method based on multiple ArUco markers
An underwater visual navigation method based on multiple ArUco markers

Underwater navigation presents crucial issues because of the rapid attenuation of electronic magnetic waves. The conventional underwater navigation methods are achieved by acoustic equip-ment, such as the ultra-short-baseline localisation systems and Doppler velocity logs, etc. However, they suffer from low fresh rate, low bandwidth, environmental disturbance and high cost. In the paper, a novel underwater visual navigation is investigated based on the multiple ArUco markers. Unlike other underwater navigation approaches based on the artificial markers, the noise model of the pose estimation of a single marker and an optimal algorithm of the multiple markers are developed to increase the precision of the method. The experimental tests are conducted in the towing tank. The results show that the proposed method is able to localise the underwater vehicle accurately.

Artificial fiducial marker, Underwater navigation, Visual localisation
Xu, Zhizun
48299771-f38a-45d6-8700-7f7bab3edcf7
Haroutunian, Maryam
f519154e-664f-40a4-9833-38c5f17f31d5
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Neasham, Jeff
66bcaecc-b93f-416f-8f2c-6a1c5608d892
Norman, Rose
6d2518aa-ece8-498f-82dc-dee5ec7b1b37
Xu, Zhizun
48299771-f38a-45d6-8700-7f7bab3edcf7
Haroutunian, Maryam
f519154e-664f-40a4-9833-38c5f17f31d5
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Neasham, Jeff
66bcaecc-b93f-416f-8f2c-6a1c5608d892
Norman, Rose
6d2518aa-ece8-498f-82dc-dee5ec7b1b37

Xu, Zhizun, Haroutunian, Maryam, Murphy, Alan J., Neasham, Jeff and Norman, Rose (2021) An underwater visual navigation method based on multiple ArUco markers. Journal of Marine Science and Engineering, 9 (12), [1432]. (doi:10.3390/jmse9121432).

Record type: Article

Abstract

Underwater navigation presents crucial issues because of the rapid attenuation of electronic magnetic waves. The conventional underwater navigation methods are achieved by acoustic equip-ment, such as the ultra-short-baseline localisation systems and Doppler velocity logs, etc. However, they suffer from low fresh rate, low bandwidth, environmental disturbance and high cost. In the paper, a novel underwater visual navigation is investigated based on the multiple ArUco markers. Unlike other underwater navigation approaches based on the artificial markers, the noise model of the pose estimation of a single marker and an optimal algorithm of the multiple markers are developed to increase the precision of the method. The experimental tests are conducted in the towing tank. The results show that the proposed method is able to localise the underwater vehicle accurately.

Text
jmse-09-01432 - Version of Record
Available under License Creative Commons Attribution.
Download (5MB)

More information

Accepted/In Press date: 11 December 2021
e-pub ahead of print date: 15 December 2021
Additional Information: Funding Information: Acknowledgments: The authors would like to acknowledge the generous support of John and Vivien Prime in funding aspects of this work.
Keywords: Artificial fiducial marker, Underwater navigation, Visual localisation

Identifiers

Local EPrints ID: 483680
URI: http://eprints.soton.ac.uk/id/eprint/483680
PURE UUID: 25bbaa8d-a3e5-4b38-9592-10c3dc602611

Catalogue record

Date deposited: 03 Nov 2023 17:51
Last modified: 17 Mar 2024 13:35

Export record

Altmetrics

Contributors

Author: Zhizun Xu
Author: Maryam Haroutunian
Author: Alan J. Murphy
Author: Jeff Neasham
Author: Rose Norman

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×