DIGITAL PHEROMONES FOR AUTONOMOUS COORDINATION OF SWARMING UAV'S

Modern UAV’s reduce the threat to human operators, but do not decrease the manpower requirements. Each aircraft requires a flight crew of one to three, so deploying large numbers of UAV’s requires committing and coordinating many human warfighters. Insects perform impressive feats of coordination without direct inter-agent coordination, by sensing and depositing pheromones (chemical scent markers) in the environment [14]. We have developed a novel technology for coordinating the movements of multiple UAV’s based on a computational analog of pheromone dynamics. The control logic is simple enough that it can be executed autonomously by a UAV, enabling a single human to monitor an entire swarm of UAV’s. This paper describes the technology, its application to UAV coordination, and the results we have obtained.

[1]  Luc Steels,et al.  Cooperation between distributed agents through self-organisation , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[2]  Luca Maria Gambardella,et al.  HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem , 1997 .

[3]  Martin Heusse,et al.  Adaptive Agent-Driven Routing and Load Balancing in Communication Networks , 1998, Adv. Complex Syst..

[4]  Tony White,et al.  Towards multi-swarm problem solving in networks , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[5]  J. Price GO TO THE ANT...... , 1969, British Journal of Psychiatry.

[6]  Guy Theraulaz,et al.  Routing in Telecommunications Networks with Ant-Like Agents , 1999, IATA.

[7]  H. Van Dyke Parunak,et al.  "Go to the ant": Engineering principles from natural multi-agent systems , 1997, Ann. Oper. Res..

[8]  E. Bonabeau,et al.  Routing in Telecommunications Networks with “ Smart ” Ant-Like Agents , 1998 .

[9]  Sven A. Brueckner,et al.  RETURN FROM THE ANT SYNTHETIC ECOSYSTEMS FOR MANUFACTURING CONTROL , 2000 .

[10]  A. Drogoul De la simulation multi-agents a la resolution collective de problemes : une etude de l'emergence de structures d'organisation dans les systemes multi-agents , 1993 .

[11]  H. V. Parunak,et al.  Tuning Synthetic Pheromones With Evolutionary Computing , 2001 .

[12]  M. K. Lauren,et al.  Describing Rates of Interaction between Multiple Autonomous Entities: An Example Using Combat Modelling , 2001, nlin/0109024.

[13]  Vittorio Maniezzo,et al.  The Ant System Applied to the Quadratic Assignment Problem , 1999, IEEE Trans. Knowl. Data Eng..

[14]  Paul Valckenaers,et al.  Manufacturing control algorithm and architecture , 1999 .

[15]  John A. Sauter,et al.  Adaptive Control of Distributed Agents Through Pheromone Techniques and Interactive Visualization , 2001 .

[16]  Alexis Drogoul When Ants Play Chess (Or Can Strategies Emerge from Tactical Behaviours?) , 1993, MAAMAW.

[17]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[18]  Barbara Webb,et al.  Swarm Intelligence: From Natural to Artificial Systems , 2002, Connect. Sci..

[19]  H. Van Dyke Parunak,et al.  A Connectionist Model for Material Handling , 1988 .

[20]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[21]  H. Van Dyke Parunak,et al.  Material Handling: A Conservative Domain for Neural Connectivity and Propagation , 1987, AAAI.

[22]  H. Van Dyke Parunak,et al.  Mechanisms and Military Applications for Synthetic Pheromones , 2001 .

[23]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[24]  J. Deneubourg,et al.  Self-organized shortcuts in the Argentine ant , 1989, Naturwissenschaften.