Distributed , Decentralized Optimization for Cooperative Control of Multi-Agent Swarm-like Systems

Award Information
Agency:
Department of Defense
Amount:
$69,957.00
Program:
STTR
Contract:
N00014-04-M-0289
Solitcitation Year:
2004
Solicitation Number:
N/A
Branch:
Navy
Award Year:
2004
Phase:
Phase I
Agency Tracking Number:
N045-005-0283
Solicitation Topic Code:
N04-T005
Small Business Information
SCIENTIFIC SYSTEMS CO., INC.
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
Y
Duns:
859244204
Principal Investigator
 Denis Garagic
 Research Engineer
 (781) 933-5355
 denisg@ssci.com
Business Contact
 Raman Mehra
Title: President
Phone: (781) 933-5355
Email: rkm@ssci.com
Research Institution
 University of California Berkeley
 Tarek Zohdi
 Mechanical Engineering, 6117 Etcheverry Hall
Berkeley, CA, 94720
 (510) 642-9172
 Nonprofit college or university
Abstract
Scientific Systems Co. Inc. and University of California at Berkeley (UCB) propose to develop, test and evaluate a computationally Distributed,Decentralized Optimization for Cooperative Control of Multi-Agent Swarm-like Systems (DOCMASS)such as groups of autonomous Unmanned Air-Vehicles (UAVs). A primary goal of the proposed work is to develop computational models amenable to high-speed simulation, design and control of multi-agent swarm-like systems, and to determine how relatively simple and controllable, interaction rules between individual agents (e.g. UAVs) can lead to sophisticated aggregate behavior which is required; for example, to accomplish autonomous reconnaissance military missions in a hostile terrain. In order to develop, test and implement the DOCMASS system, the following tasks will be carried out: (i) Develop computationally distributed and decentralized cooperative control algorithms for multi-agent swarm-like systems such as groups of UAVs operating under environmental, dynamic, kinematic and communication constraints, (ii) Perform stability analysis of multiple-agent swarm-like systems and develop performance metrics to analyze the effects of inter-vehicle communication constraints on the overall system performance, (iii) Implement and evaluate proposed algorithms on the UC Berkeley multi-agent swarm-like systems simulator, which will be modified to include for a realistic model of an UAV dynamics, sensors and a mobile military network, (iv) Simulation testing on a scenario involving up to two hundred UAVs operating in dynamic and uncertain environment while executing cooperative reconnaissance missions.

* information listed above is at the time of submission.

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