  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.
