Hybrid-VINS: Underwater Tightly-Coupled Hybrid Visual Inertial Dense SLAM for AUV

Traditional visual simultaneous localization and mapping (SLAM) methods primarily rely on passive vision, such as monocular cameras, which often exhibit reduced accuracy in localization and struggle to create dense maps in low-light underwater conditions. In this paper, a tightly-coupled hybrid visual inertial navigation system (VINS), named Hybrid-VINS, is proposed by fusing active and passive vision, which enables robust localization and dense mapping underwater. Specifically, a self-designed active vision device called underwater binocular structured light (UBSL) is integrated to provide more accurate depth estimation of the scene, enhancing the initialization and visual feature tracking process of monocular VINS. As well as it addresses the deficiency of VINS in dense mapping. In addition, a more robust hybrid vision-aided loop closure detection algorithm is proposed to mitigate issues stemming from pure passive vision misjudgments and mismatches. Furthermore, an underwater autonomous hybrid vision system is developed in both simulated and realworld underwater environments to collect various datasets for verifying the performance of Hybrid-VINS. Experimental results demonstrate that, compared with passive VINS, Hybrid-VINS holds greater promise for underwater highprecision localization and dense mapping.