An Integrated Visual Odometry System With Stereo Camera for Unmanned Underwater Vehicles
An Integrated Visual Odometry System With Stereo Camera for Unmanned Underwater Vehicles
Navigation is a challenging problem in the area of underwater unmanned vehicles, due to the significant electronmagnetic wave attenuation and the uncertainties in underwater environments. The conventional methods, mainly implemented by acoustic devices, suffer limitations such as high cost, terrain effects and low refresh rate. In this paper, a novel low-cost underwater visual navigation method, named Integrated Visual Odometry with a Stereo Camera (IVO-S), has been investigated. Unlike pure visual odometry, the proposed method fuses the information from inertial sensors and a sonar so that it is able to work in context-sparse environments. In practical experiments, the vehicle was operated to follow specific closed-loop shapes. The Integrated Visual Odoemtry with Monocular Camera (IVO-M) method and other popular open source Visual SLAMs (Simultaneous Localisation and Mappings), such as ORB-SLAM2 and VINS-Mono, have been used to provide comparative results. The cumulative error ratio is used as the quantitative evaluation method to analyse the practical test results. It is shown that the IVO-S method is able to work in underwater sparse-feature environments with high accuracy, whilst also being a low cost solution.
sensor fusion, Underwater navigation, underwater vehicles, visual-inertial odometry
71329-71343
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
(2022)
An Integrated Visual Odometry System With Stereo Camera for Unmanned Underwater Vehicles.
IEEE Access, 10, .
(doi:10.1109/ACCESS.2022.3187032).
Abstract
Navigation is a challenging problem in the area of underwater unmanned vehicles, due to the significant electronmagnetic wave attenuation and the uncertainties in underwater environments. The conventional methods, mainly implemented by acoustic devices, suffer limitations such as high cost, terrain effects and low refresh rate. In this paper, a novel low-cost underwater visual navigation method, named Integrated Visual Odometry with a Stereo Camera (IVO-S), has been investigated. Unlike pure visual odometry, the proposed method fuses the information from inertial sensors and a sonar so that it is able to work in context-sparse environments. In practical experiments, the vehicle was operated to follow specific closed-loop shapes. The Integrated Visual Odoemtry with Monocular Camera (IVO-M) method and other popular open source Visual SLAMs (Simultaneous Localisation and Mappings), such as ORB-SLAM2 and VINS-Mono, have been used to provide comparative results. The cumulative error ratio is used as the quantitative evaluation method to analyse the practical test results. It is shown that the IVO-S method is able to work in underwater sparse-feature environments with high accuracy, whilst also being a low cost solution.
Text
An_Integrated_Visual_Odometry_System_With_Stereo_Camera_for_Unmanned_Underwater_Vehicles
- Version of Record
More information
Accepted/In Press date: 23 June 2022
e-pub ahead of print date: 29 June 2022
Additional Information:
Funding Information:
The authors would like to acknowledge the generous support of John and Vivien Prime in funding aspects of this work.
Keywords:
sensor fusion, Underwater navigation, underwater vehicles, visual-inertial odometry
Identifiers
Local EPrints ID: 483679
URI: http://eprints.soton.ac.uk/id/eprint/483679
ISSN: 2169-3536
PURE UUID: 35eb9b71-23fb-45e7-bf74-f429ea0c83a3
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