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On-Board Data Handling for Longer Duration Autonomous Systems on Expeditionary Missions

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-13-P-1211
Agency Tracking Number: N13A-016-0328
Amount: $79,915.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N13A-T016
Solicitation Number: 2013.A
Solicitation Year: 2013
Award Year: 2013
Award Start Date (Proposal Award Date): 2013-07-01
Award End Date (Contract End Date): 2014-04-30
Small Business Information
20452 Scioto Terrace
Ashburn, VA -
United States
DUNS: 078727222
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 David Tolliver
 Principal Investigator
 (412) 983-3558
Business Contact
 Khurram Hassan-Shafique
Title: Member
Phone: (703) 509-0069
Research Institution
 The Ohio State University
 Per Sederberg
200K Lazenby Hall 1827 Neil Ave
Columbus, OH 43210-
United States

 (614) 292-1424
 Nonprofit College or University

This STTR Phase I project will demonstrate the feasibility and effectiveness of novel biologically-inspired computational memory models for on-board exploitation of long-duration sensor data streams to enable autonomous missions in unknown environments. The key innovation in this effort is a computationally and space-efficient computational memory model that is able to: i) handle long-duration data streams; ii) identify informative features in data streams; iii) learn from unlabeled sensor observations; iv) adapt to new scenarios; v) store learned experience in short term and long term memories and their semantic associations; and v) perform prediction and inference using the observations and the learned models. The proposed model provides a framework for modeling and solving a large variety of autonomous learning and prediction problems that arise in UAV and UGV missions. The Phase I effort will include; development of proposed models, solution of UAV and UGV problems using the models, performance optimization for SWaP constrained onboard processing, quantitative and qualitative evaluation of the proposed technologies, and demonstration of proof of concept using real-world data from multiple use-cases. The project will benefit from the Ohio State University"s expertise in computational memory modeling and Novateur Research Solution"s experience in sensor exploitation and onboard processing.

* Information listed above is at the time of submission. *

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