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An Advanced Path Planning of Clustered Multiple Robots Based on Flexible Formation

유동적인 군집대형을 기반으로 하는 군집로봇의 경로 계획

  • Wee, Sung Gil (Department of Electrical Engineering, Yeungnam Univ.) ;
  • Saitov, Dilshat (Department of Electrical Engineering, Yeungnam Univ.) ;
  • Choi, Kyung Sik (Department of Electrical System Control, Ulsan Meister High School) ;
  • Lee, Suk Gyu (Department of Electrical Engineering, Yeungnam Univ.)
  • Received : 2012.07.17
  • Accepted : 2012.09.20
  • Published : 2012.12.01

Abstract

This paper describes an advanced formation algorithm of clustered multiple robots for their navigation using flexible formation method for collision avoidance under static environment like narrow corridors. A group of clustered multiple robots finds the lowest path cost for navigation by changing its formation. The suggested flexible method of formation transforms the basic group of mobile robots into specific form when it is confronted by particular geographic feature. In addition, the proposed method suggests to choose a leader robot of the group for the obstacle avoidance and path planning. Firstly, the group of robots forms basic shapes such as triangle, square, pentagon and etc. depending on number of robots. Secondly, the closest to the target location robot is chosen as a leader robot. The chosen leader robot uses $A^*$ for reaching the goal location. The proposed approach improves autonomous formation characteristics and performance of all system.

Keywords

References

  1. Sharma, Y. K. and Bagla, A., "Security Challenges for Swarm Robotics," International Journal of Information Technology and Knowledge Management, Vol. 2, pp. 45-48, 2009.
  2. Bang, M. S., Kim, J. S., Joo, Y. H., and Park, J. B., "The Cooperate Navigation for Swarm Robot using Space Partitioning Technique," Proc. of KIEE Summer Conference, pp. 1892-1893, 2011.
  3. Yoo, Y. D., Jang, S. A., Yang, J. G., Park, J. H., and Bae, J.-H. J., "An Implementation of A Multi-Robot System Using Educational Mini-Robots," Proc. of KIISE Conference, Vol. 35, No. 1, pp. 387-390, 2008.
  4. Kim, M. K., Ko, K. E., and Sim, K. B., "Behavior Learning and Evolution of Swarm Robot based on Harmony Search Algorithm," Journal of KIIS, Vol. 20, No. 3, pp. 441-446, 2010. https://doi.org/10.5391/JKIIS.2010.20.3.441
  5. Jung, K. M., Seo, S. W., and Sim, K. B., "Mutual Localization of Swarm Robot using Particle Filter," Proc. of KIIS Spring Conference, Vol. 19, No. 1, pp. 5-8, 2009.
  6. Sim, K. B. and Lee, D. W., "Behavior Learning and Evolution of Individual Robot for Cooperative Behavior of Swarm Robot System," Journal of KIIS, Vol. 16, No. 2, pp. 131-137, 2006. https://doi.org/10.5391/JKIIS.2006.16.2.131
  7. Kornienko, S., Kornienko, O., Nagarathinam, A., and Levi, P., "From real robot swarm to evolutionary multirobot organism," IEEE Congress on Evolutionary Computation, pp. 1483-1490, 2007.
  8. Sahin, E., Girgin, S., Bayindir, L., and Turgut, A. E., "Swarm Robotics," Springer-Verlag Verlin Heidlberg, 2008.
  9. Ampatzis, C., Tuci, E., Trianni, V., and Dorigo, M., "Evolution of Signaling in a Multi-Robot System: Categorization and Communication," Adaptive Behavior, Vol. 16, No. 1, pp. 5-26, 2008. https://doi.org/10.1177/1059712307087282
  10. Heo, J. H., Hwang, S. M., Kim, C., and Lee, M. C., "Swarmming Robot Control Algorithm Design," Proc. of KIIS Conference, Vol. 20, No. 1, pp. 399-402, 2010.
  11. Das, A. K., Fierro, R., Kumar, V., Ostrowski, J. P., Spletzer, J., and Taylor, C. J., "A Vision-Based Formation Control Framework," IEEE Transactions on Robotics and Automation, Vol. 18, No. 5, pp. 813-825, 2002. https://doi.org/10.1109/TRA.2002.803463
  12. Kang, H., Lee, B., and Jang, W., "Path Planning Algorithm Using the Particle Swarm Optimization and the Improved Dijkstra Algorithm," Proceedings of KFIS Autumn Conference, Vol. 17, No. 2, pp. 176-179, 2007.
  13. Hart, P. E., Nilsson, N. J., and Raphael, B., "A Formal Basis for the Heuristic Determination of Minimum Cost Paths," IEEE Transactions on Systems Science and Cybernetics, Vol. 4, No. 2, pp. 100-107, 1968. https://doi.org/10.1109/TSSC.1968.300136
  14. Amit Patel, "Pathfinding - introduction to A*, Heuristics," http://theory.stanford.edu/-amitp/Game Programming/