Wide Aperture Imaging Sonar Reconstruction using Generative Models In this paper we propose a new framework for reconstructing underwater surfaces from wide aperture imaging sonar sequences. We demonstrate that when the leading object edge in each sonar image can be accurately triangulated in 3D, the remaining surface may be xe2x80x9cfilled inxe2x80x9d using a generative sensor model. This process generates a full threedimensional point cloud for each image in the sequence. We propose integrating these surface measurements into a cohesive global map using a truncated signed distance field (TSDF) to fuse the point clouds generated by each image. This allows for reconstructing surfaces with significantly fewer sonar images and viewpoints than previous methods. The proposed method is evaluated by reconstructing a mockup piling structure and a real world underwater piling, in a test tank environment and in the field, respectively. Our surface reconstructions are quantitatively compared to groundtruth models and are shown to be more accurate than previous stateoftheart algorithms.

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.