Reinforcement Learning and Genetic Learning Classifier Systems for Sensor Management and Adaptive Flight Control System

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,828.00
Award Year:
2002
Program:
STTR
Phase:
Phase I
Contract:
N00014-02-M-0264
Award Id:
56156
Agency Tracking Number:
N023-0175
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
20 Joyce Rd, Arlington, MA, 02474
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
James Paduano
President
(617) 968-4552
paduano@mit.edu
Business Contact:
Jeffrey Friedland
Senior Contract Administrator
(617) 253-1441
Jfried@mit.edu
Research Institution:
MIT
Jeffrey Friedland
77 Massachusetts Avenue, Room E19-750
Cambridge, MA, 02139
(617) 253-1441
Nonprofit college or university
Abstract
The work proposed here will build on current research results to develop and implement algorithms for planning trajectories of multiple Unmanned Aerial Vehicles (UAVs) working cooperatively. Their common mission is to reach a target by flying in an unknownenvironment, which they learn about through onboard sensors. The resulting sensor resource control problem is solved via dynamic programming. The algorithms to be developed and flight tested are envisioned as part of a first-of-a-kind autonomous VTOL UAVsystem being developed by NTC. This system will bring military operations closer to the goal of safe, effective operation in dangerous urban warfare environments. In addition, NTC is pursuing commercial uses of UAVs in education, newscasting, andentertainment.

* information listed above is at the time of submission.

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