Autonomous Collaborative Agents for Onboard Multi-Sensor Re-Targeting

Award Information
Agency:
National Aeronautics and Space Administration
Amount:
$599,998.00
Program:
SBIR
Contract:
NNA06BA03C
Solitcitation Year:
2004
Solicitation Number:
N/A
Branch:
N/A
Award Year:
2006
Phase:
Phase II
Agency Tracking Number:
041178
Solicitation Topic Code:
E3.05
Small Business Information
Intelligent Automation, Inc.
15400 Calhoun Drive, Suite 400, Rockville, MD, 20855-2785
Hubzone Owned:
N
Woman Owned:
Y
Socially and Economically Disadvantaged:
N
Duns:
161911532
Principal Investigator
 Goutam Satapathy
 Principal Investigator
 (301) 294-5249
 goutam@i-a-i.com
Business Contact
 Mark James
Title: Business Official
Phone: (301) 294-5221
Email: mjames@i-a-i.com
Research Institution
N/A
Abstract
In our Phase I effort we developed a prototype software-agent based framework to provide for autonomous re-targeting of sensors hosted on satellites in polar orbits, subject to standing requests and dynamic user requests. Our approach is a distributed and de-centralized, with each satellite maintaining knowledge of its sensor complement and physical capabilities as well as its schedule. Each satellite is capable of entering into negotiations for a viewing opportunity via a Contract Net type protocol; and is capable of optimizing its bid. As sensor deployment increases and autonomous vehicles become more robust, the need for a framework to support multi-sensor re-targeting in a dynamic environment involving multiple organizations becomes more acute. In our Phase 2 effort, we will extend the framework to include support for multiple types of sensor platforms as well as more sophisticated variants of the Contract Net Protocol. We will define various agent 'templates' specialized to the needs of the multi-sensor re-targeting environment. In Phase 2, the improved framework, AAMSRT, will support policy utilization to govern the sensor re-tasking. As part of the Phase 2 effort, we will engage the Open Geospatial Consortium for applicable standards, including use of SensorML, services, and OGC initiatives regarding sensor planning.

* information listed above is at the time of submission.

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