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Autonomous underwater vehicle navigation using sonar image matching based on convolutional neural network

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posted on 2023-05-20, 11:12 authored by Wenli YangWenli Yang, Fan, S, Shuxiang XuShuxiang Xu, Peter KingPeter King, Byeong KangByeong Kang, Kim, E
This paper presents an image matching algorithm based on convolutional neural network (CNN) to aid in the navigating of an Autonomous Underwater Vehicle (AUV) where external navigation aids are not available. We aim to solve the problem where traditional image feature representations and similarity learning are not learned jointly and to improve the matching accuracy of sonar images in deep ocean with dynamic backgrounds, low-intensity and high-noise scenes. In our work, the proposed CNN-based model can train the texture features of sonar images without any manually designed feature descriptors, which can jointly optimize the representation of the input data conditioned on the similarity measure being used. The validation studies show the feasibility and veracity of the proposed method for many general and offset cases using collected sonar images.

History

Publication title

IFAC PapersOnLine

Volume

52

Issue

21

Pagination

156-162

ISSN

2405-8963

Department/School

School of Information and Communication Technology

Publisher

Elsevier Ltd.

Place of publication

United Kingdom

Rights statement

© 2019, IFAC (International Federation of Automatic Control). © 2019 the authors. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) http://creativecommons.org/licenses/by-nc-nd/4.0/

Repository Status

  • Open

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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