Object perception in underwater environments: a survey on sensors and sensing methodologies
Underwater robots play a critical role in the marine industry. Object perception is the foundation for the automatic operations of submerged vehicles in dynamic aquatic environments. However, underwater perception encounters multiple environmental challenges, including rapid light attenuation, light...
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sg-ntu-dr.10356-1688532023-06-20T07:05:22Z Object perception in underwater environments: a survey on sensors and sensing methodologies Huy, Dinh Quang Sadjoli, Nicholas Azam, Abu Bakr Elhadidi, Basman Cai, Yiyu Seet, Gerald Energy Research Institute @ NTU (ERI@N) Engineering::Civil engineering Underwater Robotic Object Perception Underwater robots play a critical role in the marine industry. Object perception is the foundation for the automatic operations of submerged vehicles in dynamic aquatic environments. However, underwater perception encounters multiple environmental challenges, including rapid light attenuation, light refraction, or back-scattering effect. These problems reduce the sensing devices’ signal-to-noise ratio (SNR), making underwater perception a complicated research topic. This paper describes the state-of-the-art sensing technologies and object perception techniques for underwater robots in different environmental conditions. Due to the current sensing modalities’ various constraints and characteristics, we divide the perception ranges into close-range, medium-range, and long-range. We survey and describe recent advances for each perception range and suggest some potential future research directions worthy of investigating in this field. 2023-06-20T07:05:22Z 2023-06-20T07:05:22Z 2023 Journal Article Huy, D. Q., Sadjoli, N., Azam, A. B., Elhadidi, B., Cai, Y. & Seet, G. (2023). Object perception in underwater environments: a survey on sensors and sensing methodologies. Ocean Engineering, 267, 113202-. https://dx.doi.org/10.1016/j.oceaneng.2022.113202 0029-8018 https://hdl.handle.net/10356/168853 10.1016/j.oceaneng.2022.113202 2-s2.0-85143695840 267 113202 en Ocean Engineering © 2022 Elsevier Ltd. All rights reserved. |
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Engineering::Civil engineering Underwater Robotic Object Perception Huy, Dinh Quang Sadjoli, Nicholas Azam, Abu Bakr Elhadidi, Basman Cai, Yiyu Seet, Gerald Object perception in underwater environments: a survey on sensors and sensing methodologies |
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Underwater robots play a critical role in the marine industry. Object perception is the foundation for the automatic operations of submerged vehicles in dynamic aquatic environments. However, underwater perception encounters multiple environmental challenges, including rapid light attenuation, light refraction, or back-scattering effect. These problems reduce the sensing devices’ signal-to-noise ratio (SNR), making underwater perception a complicated research topic. This paper describes the state-of-the-art sensing technologies and object perception techniques for underwater robots in different environmental conditions. Due to the current sensing modalities’ various constraints and characteristics, we divide the perception ranges into close-range, medium-range, and long-range. We survey and describe recent advances for each perception range and suggest some potential future research directions worthy of investigating in this field. |
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Energy Research Institute @ NTU (ERI@N) |
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Energy Research Institute @ NTU (ERI@N) Huy, Dinh Quang Sadjoli, Nicholas Azam, Abu Bakr Elhadidi, Basman Cai, Yiyu Seet, Gerald |
format |
Article |
author |
Huy, Dinh Quang Sadjoli, Nicholas Azam, Abu Bakr Elhadidi, Basman Cai, Yiyu Seet, Gerald |
author_sort |
Huy, Dinh Quang |
title |
Object perception in underwater environments: a survey on sensors and sensing methodologies |
title_short |
Object perception in underwater environments: a survey on sensors and sensing methodologies |
title_full |
Object perception in underwater environments: a survey on sensors and sensing methodologies |
title_fullStr |
Object perception in underwater environments: a survey on sensors and sensing methodologies |
title_full_unstemmed |
Object perception in underwater environments: a survey on sensors and sensing methodologies |
title_sort |
object perception in underwater environments: a survey on sensors and sensing methodologies |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/168853 |
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1772825610120331264 |