Journal of the Korean Society for Aeronautical & Space Sciences (한국항공우주학회지)

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Area Search of Multiple UAV's based on Evolutionary Robotics

진화로봇공학 기반의 복수 무인기를 이용한 영역 탐색

  • Published : 2010.04.01
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Abstract

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

복수 무인기의 동시 운용을 통하여 임무 수행 효율성 제고를 꾀할 수 있으며 이를 위해서는 확장성이 용이한 제어 알고리듬을 필요로 하게 되는데 유연성, 강건성, 분산형 제어 및 자기조직화의 특징을 갖는 행동모델 기반의 무리 지능이 현실적인 대안으로 각광받고 있다. 그러나 논리적으로 행동규칙을 설계하기 어렵다는 단점을 극복하기 위하여 최근 진화로봇공학이 무인기 제어에 적용되기 시작하고 있다. 본 논문에서는 제한된 영역을 복수의 무인기로 탐색하는 임무를 진화로봇공학을 적용하여 진화시킨 신경망제어기로 수행한 결과, 직관에 의지하여 설계된 행동모델 기반의 신경망제어기에 비하여 우수한 성능을 보임을 제시하였다.

Keywords

References

  1. Crowther, B. and Riviere, X., “Flocking of Autonomous Unmanned Air Vehicles”, 17th Bristol UAV Conference, 2002.
  2. Kuiper, E. and Tehrani, S. N., “Mobility Models for UAV Group Reconnaissance Applications”, Wireless and Mobile Communications, 2006.
  3. Erignac, C. A., “An Exhaustive Swarming Search Strategy based on Distributed Pheromone Maps”, AIAA Infotech@Aerospace 2007 Conference and Exhibit, 2007.
  4. Parunak, V. D., Purcell, M., and O'connell, R., “Digital Pheromones for Autonomous Coordination Of Swarming UAV’s”, First AIAA Unmanned Aerospace Vehicles, Systems, Technologies, and Operations Conference, 2002.
  5. Bamberger, R. J., Watson, D. P., Sheidt, D. H., and Moore, K. L., “Flight Demonstrations of Unmanned Aerial Vehicle Swarming Concepts”, Johns Hopkins APL Technical Digest, Vol. 27, No. 1, 2006.
  6. Sauter, J. A., Matthews, R. M., Parunak, V. D., and Brueckner, S. A., “Performance of Digital Pheromones for Swarming Vehicle Control”, 4th International Joint Conference on Autonomous Agents and Multi-Agent Systems(AAMAS05), 2005.
  7. Gaudiano, P., Shargel, B., Bonabeau, E., and Clough, B. T., “Swarm Intelligence: a New C2 Paradigm with an Application to Control of Swarms of UAVs”, 8th ICCRTS Command and Control Research and Technology Symposium, 2003.
  8. Vincent, P. and Rubin, I., "A Framework and Analysis for Cooperative Search Using UAV Swarms", Association for Computing Machinery(ACM) Symposium on Applied Computing, 2004.
  9. Bonabeau, E., Dorigo, M., Theraulaz, G., Swarm Intelligence : from Natural to Artificial Systems, Oxford University Press, 1999, pp. 1~23.
  10. Reynolds, C. W., "Flocks, Herds, and Schools: A Distributed Behavioral Model", Computer Graphics, Vol. 21, No. 4, 1987, pp. 25~34. https://doi.org/10.1145/37402.37406
  11. 오수훈, “무리지능을 이용한 복수 무인기 제어”, 항공우주산업기술동향지, 제7권 제1호, 2009, pp. 141~152.
  12. Nolfi, S. and Floreano, D., Evolutionary Robotics; The Biology, Intelligence, and Technology of Self-Organizing Machines, 1st Ed., MIT Press, 2000.
  13. Richards, M. D., Whitley, D., and Beveridge, J. R., “Evolving Cooperative Strategies for UAV Teams”, Genetic and Evolutionary Computation Conference(GECCO), 2005.
  14. Ruini, F. and Cangelosi, A., "Distributed Control in Multi-Agent Systems: A Preliminary Model of Autonomous MAV Swarms", 11th International Conference on Information Fusion, 2008.
  15. Nardi, R. D., Holland, O., Woods, J., and Clark, A., "SwarMAV: A Swarm of Miniature Aerial Vehicles", 21st Bristol UAV Systems Conference, 2006.
  16. Floreano, D., Hauert, S., Leven, S., and Zufferey J. C., "Evolutionary Swarms of Flying Robots", International Symposium on Flying Insects and Robots, 2007.
  17. Barlow, G. J., Oh, C. K., and Grant, E., "Incremental Evolution of Autonomous Controllers for Unmanned Aerial Vehicles using Multi-objective Genetic Programming", IEEE Conference on Cybernetics and Intelligent Systems, 2004.
  18. Anderson, M. R. and Robbins, A. C., “Formation Flight as a Cooperative Game”, Proceedings of the AIAA GNC Conference and Exhibit, 1998, pp. 244~251.
  19. http://u-dynamics.com/aerosim/
  20. Mitchell, M., An Introduction to Genetic Algorithms, 1st Ed., MIT Press, 1998.

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