SWARM INTELLIGENCE AND COMMAND INTERFACE FOR COLLECTIVE OPERATION OF MILITARY UAV TEAMS

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: F33615-02-C-3222
Agency Tracking Number: 011VA-1547
Amount: $742,342.00
Phase: Phase II
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
673G, Alpha Drive, Cleveland, OH, 44143
DUNS: 557510336
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Ravi Vaidyanathan
 Director of Controls Rese
 (440) 449-5785
 raviv@orbitalresearch.com
Business Contact
 Frederick Lisy
Title: Vice President
Phone: (440) 449-5785
Email: lisy@orbitalresearch.com
Research Institution
N/A
Abstract
"Effective coordination of large groups, or "swarms" of Uninhabited Air Vehicles (UAVs) working collaboratively demands the development of control architectures that leverage emergent collective intelligence. Nature, has optimized this behavior. Inparticular, certain insect societies demonstrate an organized "swarm intelligence" beyond the capacity of any individual within their collective to understand. Although possession of similar capabilities would enhance the performance of UAV swarms, thiscannot be achieved without autonomous control strategies successfully dictating interactions between large numbers of UAVs. Further benefit could be achieved if effective tool sets could be developed allowing a single user to control an entire swarmduring battle.In Phase I Orbital Research effectively combined optimal control and emergent behavior to definitively prove the feasibility of utilizing emergent behavior to control UAVs. Algorithms were developed to allow a single operator interface to control theentire swarm. The operator could direct the vehicles and optimize their interactions with simplistic commands.In Phase II, we will further these accomplishments and produce software capable of self- programming swarm behaviors using an innovative combination of fuzzy logic, genetic algorithms, optimal control and emergent behavior. Ultimately, the operator willenter the environmental and vehicle constraints. Then, simple rule based

* Information listed above is at the time of submission. *

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