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Autonomous underwater vehicle navigation using sonar image matching based on convolutional neural network
Citation
Yang, W and Fan, S and Xu, S and King, P and Kang, B and Kim, E, Autonomous underwater vehicle navigation using sonar image matching based on convolutional neural network, IFAC PapersOnLine, 52, (21) pp. 156-162. ISSN 2405-8963 (2019) [Refereed Article]
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Copyright 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/
DOI: doi:10.1016/j.ifacol.2019.12.300
Abstract
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.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | sonar image matching, convolutional neural network, feature extraction, AUV, teach-and-repeat path following |
| Research Division: | Information and Computing Sciences |
| Research Group: | Computer vision and multimedia computation |
| Research Field: | Image processing |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Information systems, technologies and services not elsewhere classified |
| UTAS Author: | Yang, W (Dr Wenli Yang) |
| UTAS Author: | Xu, S (Dr Shuxiang Xu) |
| UTAS Author: | King, P (Mr Peter King) |
| UTAS Author: | Kang, B (Professor Byeong Kang) |
| UTAS Author: | Kim, E (Miss Eonjoo Kim) |
| ID Code: | 137586 |
| Year Published: | 2019 |
| Web of Science® Times Cited: | 13 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2020-02-20 |
| Last Modified: | 2020-05-18 |
| Downloads: | 22 View Download Statistics |
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