From Light to Position: An Underwater Visual–Inertial Positioning Method Using Visible Light

The reliable localization is essential for the efficiency and safety of autonomous underwater operations. In this study, we propose a novel localization framework centered on a strapdown inertial navigation system (INS), which receives high-precision pose corrections from image-based visible-light positioning (VLP). A structured LED array is deployed as a stable underwater positioning reference, and an adaptive optical signal processing method is developed to enhance the extraction of light-spot features under challenging scenarios. To address the distortions introduced by cross-medium refraction, we introduce a compensation model that restores accurate camera pose estimation without the need for cumbersome recalibration. Extensive experimental evaluations demonstrate that the proposed system achieves millimeter-level accuracy under favorable scenarios and maintains centimeter-level robustness in unfavorable observation scenarios. Owing to its high precision, robustness, and cost effectiveness, the proposed approach holds significant promise for advancing autonomous underwater navigation and next-generation intelligent robotic systems.