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

This development would improve off-GPS navigation performance for unmanned and manned underwater vehicles, including UUVs, ,AUVs, USVs and more and with automatic, real-time Simultaneous Localization and Mapping (SLAM)navigation aiding using matching of terrain features to prove corrections that reduce the drift in the vehicle's INS thereby improving mission performance while reducing the need for costly post-acquisition processing, or re-survey.  The development will be based on Oceanic Imaging Consultants' (OIC's) commercially available product, well established in the industry, that performs manual feature matching for sidescan and swath bathymetry data utilizing a SLAM algorithm in post-acquisition mode. The tasks proposed in this effort are 1) automation of feature detection, extraction and matching, 2) optimization of matched feature selection to minimize outlier-induced noise, and 3) modification or replacement of the current working SLAM algorithm to run incrementally, and in real-time. This would solve a non-trivial problem for existing government programs, and is supported enthusiastically by existing and future OIC customers. OIC's proposes that the phase I desktop and testing effort be followed by a 6 month effort of in-depth testing and refinement, with collection of purpose-built test data.  The result would be algorithms ready for implementation and documentation in production code, interfaced to the Navy's Unmanned Maritime Autonomy Architecture (UMAA), in preparation for trials on Government UUVs and commercial vehicles.