Autonomous Navigation-Aiding of Unmanned Underwater Vehicles using Real-Time SLAM

This effort seeks to improve off-GPS navigation performance for underwater vehicles, both manned and unmanned, including UUVs, AUVs, ROVs and manned subs, with automatic, real-time feature-based navigation known as SLAM - Simultaneous Localization and Mapping. ĀSLAM navigation aiding uses matching of terrain features to prove corrections that reduce the drift in the vehicles Inertial Navigation System (INS), thereby improving mission performance while reducing the need for costly post-acquisition processing, or re-survey. ĀThen development Āwill be based on Oceanic Imagining Consultants' (OIC's) commercially available product, well established in the industry, that performs manual feature matching for sidescan and swath bathymetryĀdata using a SLAM algorithm tin post-acquisition mode. The tasks outlined in this proposal are 1) getting the current or updated SLAM algorithm to run in real-time, 2) addition of support for processing of Forward-Look Sonar data in CleanSweep, 3) automation of feature-detection, extraction and matching, and 4) optimization of matched feature selection to minimize outlive-induced noise in re-estimation of navigation trajectory. ĀThis would solve a non-trivial problem for existing government programs, and is supported enthusiastically by existing and future OIC customers on theĀcommercial side. The result will be algorithms ready for implementation and utilization in production code, interfaced to the Navy's Unmanned Maritime Autonomy Architecture (UMAA), in preparation for trials on Government UUV's and commercial vehicles.