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Cited by 65Underwater Vehicles and Communication SystemsRobotics and Sensor-Based LocalizationMaritime Navigation and Safety

A Survey on Visual Navigation and Positioning for Autonomous UUVs

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Qin, Jiangying, Li, Ming, Li, Deren, Zhong, Jiageng, Yang, Ke·2022·Remote Sensing
DOI 10.3390/rs14153794
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Abstract

Autonomous navigation and positioning are key to the successful performance of unmanned underwater vehicles (UUVs) in environmental monitoring, oceanographic mapping, and critical marine infrastructure inspections in the sea. Cameras have been at the center of attention as an underwater sensor due to the advantages of low costs and rich content information in high visibility ocean waters, especially in the fields of underwater target recognition, navigation, and positioning. This paper is not only a literature overview of the vision-based navigation and positioning of autonomous UUVs but also critically evaluates the methodologies which have been developed and that directly affect such UUVs. In this paper, the visual navigation and positioning algorithms are divided into two categories: geometry-based methods and deep learning-based. In this paper, the two types of SOTA methods are compared experimentally and quantitatively using a public underwater dataset and their potentials and shortcomings are analyzed, providing a panoramic theoretical reference and technical scheme comparison for UUV visual navigation and positioning research in the highly dynamic and three-dimensional ocean environments.

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Cited by

Sorted by citations

Authors
Qin, J., Li, M., Li, D., Zhong, J., & Yang, K.
Affiliations
  • Wuhan University (CN)
  • ETH Zurich (CH)
Corresponding author
Li, Ming
ORCID
Venue
Remote Sensing
Publisher
MDPI AG
Published
2022-08-06
Volume
14
Issue
15
Pages
3794
ISSN
2072-4292 (ISSN-L)
DOI
10.3390/rs14153794
OpenAlex
W4290755992
Cited by
65
References
13
Citations by year
2026: 11 · 2025: 20 · 2024: 17 · 2023: 16 · 2022: 1
FWCI
6.55
Type
journal article
Language
en
Open access
Licence
Locations
  • Remote Sensing (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
  • ETH Zürich Research Collection
Funders
  • National Key R&D Program of China (2018YFB0505400, 41901407, S202210486307)
  • National Natural Science Foundation of China (NSFC) (2018YFB0505400, 41901407, S202210486307)
  • the College Students’ Innovative Entrepreneurial Training Plan Program (2018YFB0505400, 41901407, S202210486307)
Topics
  • Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
  • Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
  • Physical Sciences › Engineering › Ocean Engineering › Maritime Navigation and Safety
Keywords
unmanned underwater vehicles, visual navigation, underwater localization, visual localization, underwater camera, autonomous underwater vehicles

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