| Autor: |
Lin, Xiaomin, Jha, Nitesh, Joshi, Mayank, Karapetyan, Nare, Aloimonos, Yiannis, Yu, Miao |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
OCEANS 2022, Hampton Roads, 2022, pp. 1-6 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/OCEANS47191.2022.9977233 |
| Popis: |
Oysters are the living vacuum cleaners of the oceans. There is an exponential decline in the oyster population due to over-harvesting. With the current development of the automation and AI, robots are becoming an integral part of the environmental monitoring process that can be also utilized for oyster reef preservation. Nevertheless, the underwater environment poses many difficulties, both from the practical - dangerous and time consuming operations, and the technical perspectives - distorted perception and unreliable navigation. To this end, we present a simulated environment that can be used to improve oyster reef monitoring. The simulated environment can be used to create photo-realistic image datasets with multiple sensor data and ground truth location of a remotely operated vehicle(ROV). Currently, there are no photo-realistic image datasets for oyster reef monitoring. Thus, we want to provide a new benchmark suite to the underwater community. |
| Databáze: |
arXiv |
| Externí odkaz: |
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