Underwater target localization uses real-time sensory measurements to estimate the position of underwater objects of interest, providing critical feedback information for underwater robots. While acoustic sensing is the most acknowledged method in underwater robots and possibly the only effective approach for long-range underwater target localization, such a sensing modality generally suffers from low resolution, high cost and high energy consumption, thus leading to a mediocre performance when applied to close-range underwater target localization. On the other hand, optical sensing has attracted increasing attention in the underwater robotics community for its advantages of high resolution and low cost, holding a great potential particularly in close-range underwater target localization. However, most existing studies in underwater optical sensing are restricted to specific types of targets due to the limited training data available. In addition, these studies typically focus on the design of estimation algorithms and ignore the influence of illumination conditions on the sensing performance, thus hindering wider applications in the real world. To address the aforementioned issues, this paper proposes a novel target localization method that assimilates both optical and acoustic sensory measurements to estimate the 3D positions of close-range underwater targets. A test platform with controllable illumination conditions is designed and developed to experimentally investigate the proposed multi-modal sensing approach. A large vision model is applied to process the optical imaging measurements, eliminating the requirement for training data acquisition, thus significantly expanding the scope of potential applications. Extensive experiments are conducted, the results of which validate the effectiveness of the proposed underwater target localization method.

翻译：水下目标定位利用实时传感测量估计感兴趣水下目标的位置，为水下机器人提供关键的反馈信息。声学感知是水下机器人领域最公认的方法，也可能是远距水下目标定位的唯一有效手段，但此类传感模态通常存在分辨率低、成本高和能耗大等问题，导致其在近距水下目标定位应用中表现平庸。另一方面，光学感知凭借高分辨率和低成本的优势，在水下机器人领域日益受到关注，尤其在近距水下目标定位方面展现出巨大潜力。然而，现有水下光学感知研究大多受限于特定类型的目标，原因在于可用训练数据有限。此外，这些研究通常侧重于估计算法的设计，而忽略了光照条件对感知性能的影响，这阻碍了其在实际应用中的广泛推广。为解决上述问题，本文提出一种新型目标定位方法，融合光学与声学传感测量来估计近距水下目标的三维位置。我们设计并开发了具备可控光照条件的测试平台，以实验研究提出的多模态感知方法。利用大视觉模型处理光学成像测量，消除对训练数据采集的需求，从而显著拓展了潜在应用范围。广泛实验验证了所提水下目标定位方法的有效性。