Underwater Dense Mapping with the First Compact 3D Sonar

In the past decade, the adoption of compact 3D range sensors, such as LiDARs, has driven the developments of robust state-estimation pipelines, making them a standard sensor for aerial, ground, and space autonomy. Unfortunately, poor propagation of electromagnetic waves underwater, has limited the visibility-independent sensing options of underwater state-estimation to acoustic range sensors, which provide 2D information including, at-best, spatially ambiguous information. This paper, to the best of our knowledge, is the first study examining the performance, capacity, and opportunities arising from the recent introduction of the first compact 3D sonar. Towards that purpose, we introduce calibration procedures for extracting the extrinsics between the 3D sonar and a camera and we provide a study on acoustic response in different surfaces and materials. Moreover, we provide novel mapping and SLAM pipelines tested in deployments in underwater cave systems and other geometrically and acoustically challenging underwater environments. Our assessment showcases the unique capacity of 3D sonars to capture consistent spatial information allowing for detailed reconstructions and localization in datasets expanding to hundreds of meters. At the same time it highlights remaining challenges related to acoustic propagation, as found also in other acoustic sensors. Datasets collected for our evaluations would be released and shared with the community to enable further research advancements.

Mapping the Catacombs: An Underwater Cave Segment of the Devil's Eye System

This paper presents a framework for mapping underwater caves. Underwater caves are crucial for fresh water resource management, underwater archaeology, and hydrogeology. Mapping the cave's outline and dimensions, as well as creating photorealistic 3D maps, is critical for enabling a better understanding of this underwater domain. In this paper, we present the mapping of an underwater cave segment (the catacombs) of the Devil's Eye cave system at Ginnie Springs, FL. We utilized a set of inexpensive action cameras in conjunction with a dive computer to estimate the trajectories of the cameras together with a sparse point cloud. The resulting reconstructions are utilized to produce a one-dimensional retract of the cave passages in the form of the average trajectory together with the boundaries (top, bottom, left, and right). The use of the dive computer enables the observability of the z-dimension in addition to the roll and pitch in a visual/inertial framework (SVIn2). In addition, the keyframes generated by SVIn2 together with the estimated camera poses for select areas are used as input to a global optimization (bundle adjustment) framework -- COLMAP -- in order to produce a dense reconstruction of those areas. The same cave segment is manually surveyed using the MNemo V2 instrument, providing an additional set of measurements validating the proposed approach. It is worth noting that with the use of action cameras, the primary components of a cave map can be constructed. Furthermore, with the utilization of a global optimization framework guided by the results of VI-SLAM package SVIn2, photorealistic dense 3D representations of selected areas can be reconstructed.