Combat Systems of the Future

Award Information
Agency:
Department of Defense
Amount:
$3,568,940.00
Program:
SBIR
Contract:
N00024-07-C-4117
Solitcitation Year:
2005
Solicitation Number:
2005.3
Branch:
Navy
Award Year:
2007
Phase:
Phase II
Agency Tracking Number:
N053-149-0232
Solicitation Topic Code:
N05-149
Small Business Information
RITE-SOLUTIONS
110 W. Broad Street, P.O. Box 1060, Pawcatuck, CT, 06379
Hubzone Owned:
Y
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
125370176
Principal Investigator
 John DePrimo
 Senior Systems Engineer
 (401) 847-3399
 jdeprimo@rite-solutions.com
Business Contact
 Linda Edwards
Title: Chief Financial Officer
Phone: (860) 599-1938
Email: ledwards@rite-solutions.com
Research Institution
N/A
Abstract
During Phase I, the Rite-Solutions team has explored enabling technologies critical to the Navy's reduced manning objectives. They include mission- and intent-focused displays; expert systems; robust, high availability architectures that result in minimal or no operator maintenance during a mission; and constraint based reasoning. In the interest of constraining our initial look to a manageable subset of the overall combat system, we have determined that it is feasible to develop a Command Decision Support System that provides high level advisory decision support and human interface capabilities to ship's command personnel as part of our Phase II effort. The system concepts evolved using a highly-structured Humans Systems Integration process and employs advanced AI-based and visualization technologies. Commercial high availability architectures are an essential enabler for reduced manning and several approaches have been explored. Leveraging our success with 24/7 commercial gaming systems, we will develop the foundation for a high-availability combat system architecture consistent with optimized onboard performance as well as offboard GIG/IA compliance. Constraint based reasoning approaches will be further investigated and demonstrated during Phase II as a means to reduce the level of uncertainty thereby transferring cognitive workload from human to machine.

* information listed above is at the time of submission.

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