| Autor: |
Dinh Quang Huy, Nicholas Sadjoli, Abu Bakr Azam, Basman Elhadidi, Yiyu Cai, Gerald Seet |
| Přispěvatelé: |
Energy Research Institute @ NTU (ERI@N) |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Ocean Engineering. 267:113202 |
| ISSN: |
0029-8018 |
| DOI: |
10.1016/j.oceaneng.2022.113202 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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