International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Behavior Learning of Swarm Robot System using Bluetooth Network

  • Seo, Sang-Wook (School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Yang, Hyun-Chang (School of Electrical and Electronic Engineering, Chung-Ang University) ;
  • Sim, Kwee-Bo (School of Electrical and Electronic Engineering, Chung-Ang University)
  • Published : 2009.03.01
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Abstract

With the development of techniques, robots are getting smaller, and the number of robots needed for application is greater and greater. How to coordinate large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot Systems (SRS) is a system that independent autonomous robots in the restricted environments infer their status from pre-assigned conditions and operate their jobs through the cooperation with each other. In the SRS, a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Especially, in order to cooperate with other robots, communicating with other robots is one of the essential elements. Because Bluetooth has many advantages such as low power consumption, small size module package, and various standard protocols, it is rated as one of the efficient communicating technologies which can apply to small-sized robot system. In this paper, we will develop Bluetooth communicating system for autonomous robots. And we will discuss how to construct and what kind of procedure to develop the communicating system for group behavior of the SRS under intelligent space.

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References

  1. Sang-Wook Seo, Kwang-Eun Ko, Hyun-Chang Yang and Kwee-Bo Sim, "Behavior Leaming and Evolution of Swarm Robot System using SVM," lntemational Comference on Control, Automation and Systems 2007, pp. 1238-1242
  2. Spiros Kapetanakis, Daniel Kudenko, "Reinforcement learning of coordination in cooperative multi-agent systems," Eighteenth national conference on Artificial intelligence, pp. 326-331, 2002
  3. Kwee-Bo Sim, Dong-Wook Lee, "Behavior leaming and evolution of individual robot for cooperative behavior of swann robot system," Joumal of Fuzzy Logic and lntelligent Systems Society, vol. 16, no. 2, pp. 131-136, 2006 https://doi.org/10.5391/JKIIS.2006.16.2.131
  4. H. Asama, T. Fukuda, T. Arai, and I. Endo (Eds), Distributed Autonomous Robotic Systems, Springer Verlag, 1994
  5. H. Asama, T. Fukuda, T. Arai, and I. Endo (eds)， Distributed Autonomous Robotic Systems 2. Springer Verlag, 1996
  6. E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence - From Natural to Artificial Systems -, Oxford University Press, 1999
  7. J. Kennedy, R.C. Eberhart, Swarm Intelligence, Academic Press, 2001
  8. Specification of the Bluetooth System Ver 1.1, Bluetooth SIG., http://www.bluetooth.com, 2001
  9. Specification of thε Bluetooth System Ver 1.2, Bluetooth SIG., http://www.bluetooth.com. 2003
  10. J. Michael Ram, Chuan Pang, Dabid C. Yen and Jon Chen, "Exploring the implementation and application of Bluetooth technology in the shipping industry," Computer Standards & interfaces, vol. 31, No. 1, pp. 48-55, 2009 https://doi.org/10.1016/j.csi.2007.10.006
  11. BlueTool for HCI User Manual, Bluetooth Lab., http://www.bluetoothlab.com
  12. G. Tan, A. Miu, J. Guttag and H. Balakrishnan, "Forming Scatternets from Bluetooth Personal Area Networks," In MlT Technical Report MIT LCS-TR-826, 2001
  13. C. Lay and K.Y. Siu, "A Bluetooth Scattemet Formation AIgorithm," Proc. of the Conf. on Global Telecommunications, vol. 5, pp. 2864-2869, 2001
  14. C. Law, A.K. Mehta and K.Y. Siu, "Performnance of a New Bluetooth Scatternet Fonnation Protocol," Proc. Of ACM Symp. on Mobile Ad Hoc Networking and Computing, pp. 182-192, 2001