论文标题

牡蛎:用于增强牡蛎礁监测的水下模拟

OysterSim: Underwater Simulation for Enhancing Oyster Reef Monitoring

论文作者

Lin, Xiaomin, Jha, Nitesh, Joshi, Mayank, Karapetyan, Nare, Aloimonos, Yiannis, Yu, Miao

论文摘要

牡蛎是海洋的活真空吸尘器。由于过度收获,牡蛎人口呈指数下降。随着自动化和AI的当前发展,机器人正在成为环境监测过程中不可或缺的一部分,该过程也可以用于牡蛎礁保存。然而,水下环境构成了许多困难,包括实用的危险和耗时的操作以及技术观点 - 扭曲的感知和不可靠的导航。为此,我们提供了一个模拟环境,可用于改善牡蛎礁监测。模拟环境可用于创建具有多个传感器数据和远程操作车辆(ROV)的地面真相位置的照片真实的图像数据集。当前,没有用于牡蛎礁监视的照片真实图像数据集。因此,我们希望为水下社区提供新的基准套件。

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.

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