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Introduction to RoboCup Research in Japan

  • Yoichiro Maeda
Conference paper
  • 637 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3131)

Abstract

RoboCup (Robot World Cup Initiative) is the most famous soccer robot competition in the world. However, RoboCup was originally established as an international joint project to promote AI, robotics, and related field. To go toward this aim, the soccer game is selected as a primary domain in RoboCup and soccer game competitions and international conferences have been organized at different places of the world every year since 1997 [1]-[6]. Currently, about 35 countries and 3,000 researchers are participating in the RoboCup project. The final goal of the RoboCup project is to develop a team of fully autonomous humanoid robot soccer players, according to the official rule of the FIFA, that can win against the human World Cup champion team until 2050.

Keywords

Mobile Robot Real Robot Soccer Game Robot Soccer Omnidirectional Vision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Kitano, H. (ed.): RoboCup 1997. LNCS, vol. 1395. Springer, Heidelberg (1998)Google Scholar
  2. 2.
    Asada, M. (ed.): RoboCup 1998. LNCS (LNAI), vol. 1604. Springer, Heidelberg (1999)Google Scholar
  3. 3.
    Veloso, M., Pagello, E., Kitano, H. (eds.): RoboCup 1999. LNCS (LNAI), vol. 1856. Springer, Heidelberg (2000)Google Scholar
  4. 4.
    Stone, P., Balch, T., Kraetzschmar, G. (eds.): RoboCup 2000. LNCS (LNAI), vol. 2019. Springer, Heidelberg (2001)zbMATHGoogle Scholar
  5. 5.
    Birk, A., Coradeschi, S., Tadokoro, S. (eds.): RoboCup 2001. LNCS (LNAI), vol. 2377. Springer, Heidelberg (2002)zbMATHGoogle Scholar
  6. 6.
    Kaminka, G.A., Lima, P.U., Rojas, R. (eds.): RoboCup 2002. LNCS (LNAI), vol. 2752. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  7. 7.
    Mackworth, A.: On Seeing Robots, Computer Vision: System, Theory, and Applications, pp. 1–13. World Scientific Press, Singapore (1993)Google Scholar
  8. 8.
    Tsuzaki, R., Yoshida, K.: Motion Control Based on Fuzzy Potential Method for Autonomous Mobile Robot with Omnidirectional Vision. J. of the Robotics Society of Japan, 656–662 (2003) (in Japanese)Google Scholar
  9. 9.
    Kougo, J., Fujii, H., Yoshida, K.: Design Method of an Action-Integrator for Cooperative Soccer Robot. In: Symp. of the Robotics Society of Japan (RSJ 2002) ,1B38, CD-ROM (2002) (in Japanese)Google Scholar
  10. 10.
    Asada, M., Noda, S., Tawaratumida, S., Hosoda, K.: Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning. Machine Learning 23, 279–303 (1996)Google Scholar
  11. 11.
    Takahashi, Y., Asada, M.: Multi-Controller Fusion in Multi-Layered Reinforcement Learning. In: International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2001), pp. 7–12 (2001)Google Scholar
  12. 12.
    Uchibe, E., Yanase, M., Asada, M.: Behavior Generation for a Mobile Robot Based on the Adaptive Fitness Function. In: Proc. of Intelligent Autonomous Systems (IAS-6), pp. 3–10 (2000)Google Scholar
  13. 13.
    Enokida, S., Ohashi, T., Yoshida, T., Ejima, T.: Extended Q-Learning: Reinforcement Learning Using Self-Organized State Space. In: Stone, P., Balch, T., Kraetzschmar, G.K. (eds.) RoboCup 2000. LNCS (LNAI), vol. 2019, pp. 129–138. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  14. 14.
    RoboCup Federation.: Robocup Official Site, http://www.robocup.org/

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yoichiro Maeda
    • 1
  1. 1.Department of Human and Artificial Intelligent Systems, Faculty of EngineeringFukui UniversityFukuiJapan

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