SunBeam: Automatic Postprocessing of Underwater Mapping Data

We propose the SunBeam underwater data postprocessor to provide rapid, automated generation of large scale environmental models from a wide variety of underwater sensors. This automated software suite will leverage over 15 years of experience at Sunfish, Inc. and Stone Aerospace with advanced, fully 3-dimensional (3D) Simultaneous Localization and Mapping (SLAM) systems used as part of Unmanned Underwater Vehicle (UUV) onboard navigation systems.  Currently, processing of seabed data into large-scale 3D models is prohibitively resource intensive. There are many methods to obtain large underwater data sets using a variety of platforms and sensing modalities. This data contains a variety of systematic errors, random noise, and outlier measurements. State-of-the-art processing of such data relies on trained human operators both to clean the data and optimize automated processing parameters. No generalized, automated framework for generation of 3D models from underwater data currently exists. Finally, state-of-the-art underwater environmental models are typically not fully 3D and generally achieve resolutions on the order of 1e-9 of the mapped volume. With SunBeam, we propose to scale our existing processing algorithms—which can already generate full 3D environmental models on small-scale multibeam sonar datasets with modest human intervention—to a system which can incorporate a wide variety of long- and short-range underwater sensors. We will assimilate data on the scale of 100 km2, 1500 m vertical variation, and 5 mm resolution, and fully automate the processing of an environmental model within 2 days.  Phase I will investigate high-risk portions of our approach to determine its feasibility, and develop a prototype implementation, which will incorporate multibeam sonar and monocular camera data from a variety of sensor manufacturers. Our approach will leverage our current fully-3D processing system which is already optimized to rapidly (up to real time) produce environmental models used for UUV localization, planning, and simulation. We will also leverage our existing SUNFISH UUV which can autonomously explore and map complex 3D underwater environments using a multibeam sonar, inertial sensors, Doppler velocity log, and high definition camera. This platform will enable us to generate new camera and sonar datasets for testing and training the prototype implementation, allowing for rapid, iterative development of the technology. The two highest-risk elements of this development are (1) scaling the data, processing, and output model to resolutions of 1e-18 of the mapped volume and (2) automating processing to completely remove humans from the loop. To generate a continuous, high-resolution 3D model, both long and short range sensors must be used, and gaps in the model must be filled. Our Phase I development plan will focus on the following four technical objectives: adding new sensing modalities, automation, computational scaling, and filling in gaps.