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Real-Time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments

机译:用于浑浊和动态水下环境的实时单眼视觉里程表

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摘要

In the context of underwater robotics, the visual degradation induced by the medium properties make difficult the exclusive use of cameras for localization purpose. Hence, many underwater localization methods are based on expensive navigation sensors associated with acoustic positioning. On the other hand, pure visual localization methods have shown great potential in underwater localization but the challenging conditions, such as the presence of turbidity and dynamism, remain complex to tackle. In this paper, we propose a new visual odometry method designed to be robust to these visual perturbations. The proposed algorithm has been assessed on both simulated and real underwater datasets and outperforms state-of-the-art terrestrial visual SLAM methods under many of the most challenging conditions. The main application of this work is the localization of Remotely Operated Vehicles used for underwater archaeological missions, but the developed system can be used in any other applications as long as visual information is available.
机译:在水下机器人技术的背景下,由中等性质引起的视觉退化使得难以将摄像机专用于定位。因此,许多水下定位方法是基于与声学定位相关联的昂贵的导航传感器。另一方面,纯粹的视觉定位方法在水下定位中显示出巨大的潜力,但挑战性的条件(例如存在浑浊和动态)仍然难以解决。在本文中,我们提出了一种新的视觉里程计方法,旨在对这些视觉干扰具有鲁棒性。该拟议算法已在模拟和真实水下数据集上进行了评估,在许多最具挑战性的条件下,其性能均超过了最新的地面视觉SLAM方法。这项工作的主要应用是用于水下考古任务的遥控车的本地化,但是只要有视觉信息,该开发的系统就可以用于任何其他应用。

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