Contour based Reconstruction of Underwater Structures Using Sonar, Visual, Inertial, and Depth Sensor This paper presents a systematic approach on realtime reconstruction of an underwater environment using Sonar, Visual, Inertial, and Depth data. In particular, low lighting conditions, or even complete absence of natural light inside caves, results in strong lighting variations, e.g., the cone of the artificial video light intersecting underwater structures, and the shadow contours. The proposed method utilizes the well defined edges between well lit areas and darkness to provide additional features, resulting into a denser 3D point cloud than the usual point clouds from a visual odometry system. Experimental results in an underwater cave at Ginnie Springs, FL, with a custommade underwater sensor suite demonstrate the performance of our system. This will enable more robust navigation of autonomous underwater vehicles using the denser 3D point cloud to detect obstacles and achieve higher resolution reconstructions.

SVIn2: An Underwater SLAM System using Sonar, Visual, Inertial, and Depth Sensor This paper presents a novel tightlycoupled keyframebased Simultaneous Localization and Mapping (SLAM) system with loopclosing and relocalization capabilities targeted for the underwater domain.Our previous work, SVIn, augmented the stateoftheart visualinertial state estimation package OKVIS to accommodate acoustic data from sonar in a nonlinear optimizationbased framework. This paper addresses drift and loss of localization xe2x80x93 one of the main problems affecting other packages in underwater domain xe2x80x93 by providing the following main contributions: a robust initialization method to refine scale using depth measurements, a fast preprocessing step to enhance the image quality, and a realtime loopclosing and relocalization method using bag of words (BoW). An additional contribution is the addition of depth measurements from a pressure sensor to the tightlycoupled optimization formulation. Experimental results on datasets collected with a custommade underwater sensor suite and an autonomous underwater vehicle from challenging underwater environments with poor visibility demonstrate performance never achieved before in terms of accuracy and robustness.