Coordinated Control of Multi-Agent Systems in Rapidly Varying Environments

Award Information
Agency:
National Aeronautics and Space Administration
Branch
n/a
Amount:
$599,974.00
Award Year:
2005
Program:
STTR
Phase:
Phase II
Contract:
NNA05AC51C
Agency Tracking Number:
030166
Solicitation Year:
2003
Solicitation Topic Code:
T1.01
Solicitation Number:
n/a
Small Business Information
Scientific Systems Company, Inc.
500 West Cummings Park Suite 3000, Woburn, MA, 01801-6580
Hubzone Owned:
N
Socially and Economically Disadvantaged:
Y
Woman Owned:
N
Duns:
859244204
Principal Investigator:
Eliot Li
Principal Investigator
(781) 933-5355
eliot@ssci.com
Business Contact:
Robert Simpson
Controller
(781) 933-5355
accts@ssci.com
Research Institution:
Brigham Young University
Matthew Maddox
Office of Research & Creative Activities, A-261 ASB
Provo, UT, 84602
(801) 422-1461
Domestic nonprofit research organization
Abstract
The main objective of this Phase II STTR project is to develop advanced control algorithms that enable multiple autonomous agents to perform complex tasks in rapidly changing environment cooperatively. We plan to use the forest fire monitoring mission to demonstrate the benefits of the proposed technology. The mission concept involves using multiple Low Altitude Short Endurance (LASE) Unmanned Aerial Vehicles (UAVs) equipped with camera and wireless communication modem to monitor a forest fire. Advantages of using LASE UAVs for this mission include flexible deployment, capability to collect high resolution imagery data, more frequent data update to the ground crew, and significantly lower cost than existing means (e.g. manned helicopter). Since the fire monitoring mission shares many characteristics of future NASA space exploration or Earth observing missions that require autonomous control of multiple satellite or vehicles, the proposed technology is expected to be applicable in those missions as well. Our technical objectives for this project are: (i) Develop autonomous decentralized cooperative control scheme; (ii) Develop payload driven perimeter tracking algorithms; (iii) Develop autonomous data acquisition and rectification algorithms; (iv) Develop intelligent fleet management algorithm, and (v) Demonstrate the feasibility of the proposed system through flight tests on prototype UAV hardware.

* information listed above is at the time of submission.

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