A Study of Communication Emergence among Mobile Robots : Simulations of Intention Transmission

  • Kuniaki Kawabata
  • Hajime Asama
  • Masayuki Tanaka


Purpose of this study is to realize communication emergence among multiple robots. An important role of communication in multi-agent system is to make it possible to control the other agents based on intention transmission. We consider that multiple robots system can be more and more adaptable by treating communication as one of behavior. We discuss the method of how the robots can learn appropriate actions including communication to adapt the environment without giving communication manner. In this paper, we attempt computer simulations of collision avoidance as an example of cooperative task and discuss the results.


Mobile Robot Collision Avoidance Multiple Robot Communication Emergence Semi Markov Decision Process 
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  1. 1.
    Y. Ishida, H. Asama, K. Ozaki, A. Matsumoto, I. Endo, Design of Communication System and Development of a Simulator for an Autonomous and Decen-trized Robot System, Journal of Robotics Society of Japan, 10(4), 1992, 544–551 (in Japanese)CrossRefGoogle Scholar
  2. 2.
    N. Hutin, C. Pegard, E. Brassart, A Communication Strategy for Cooperative Robots, Proc. of IEEE/RSJ Intl. Conference on Inteligent Robots and Systems, 1998, 114–119Google Scholar
  3. 3.
    H. Ynaco, L. A. Stein, An Adaptive Communication Protocol for Cooperating Mobile Robots, From Animals to Animats 2, 1993, 478–485Google Scholar
  4. 4.
    A. Billard, G. Hayes, Learning to Communicate Through Imitation in Autonomous Robots, Artificial Neural Networks — ICANN’97, 1997, 763–768Google Scholar
  5. 5.
    M. Asada, A. Noda, K. Tawaratsumida, K. Hosoda, Purposive Behavior Aquisition for a Robot by Vision-Based Reinforcement Learning, Journal of Robotics Society of Japan, 13(1), 1995, 68–74 (in Japanese)CrossRefGoogle Scholar
  6. 6.
    R. S. Sutton, A. G. Barto, Reinforcement Learning -An Introduction- (MIT Press, Cambridge, Massachusetts, 1998)Google Scholar
  7. 7.
    H. Asama, M. Sato, L. Bogoni, H. Kaetsu, I. Endo, Development of an Omni-Directional Mobile Robot with 3 DOF Decoupling Drive Mechanism, Proc. of International Conference on Robotics and Automation, 1995, 1925–1930Google Scholar
  8. 8.
    K. Yokota, K. Ozaki, A. Matsumoto, K. Kawabata, H. Kaetsu, H. Asama, Omni-directional Autonomous Robots Cooperatinng for Team Play, RoboCup-97: Robot Soccer World Cup I (Springer Verlag, Tokyo, 1998), 333–347Google Scholar
  9. 9.
    M. Hoshino, H. Asama, K. Kawabata, Y. Kunii, I. Endo, Communication Learning for Cooperation among Autonomous Robots, Proc. of IEEE International Conference on Industrial Electronics, Control and Instrumentation, 2000, SS38-SOR-4Google Scholar

Copyright information

© Springer-Verlag Tokyo 2002

Authors and Affiliations

  • Kuniaki Kawabata
    • 1
  • Hajime Asama
    • 1
  • Masayuki Tanaka
    • 2
  1. 1.Advanced Engineering CenterRIKENWako, SaitamaJapan
  2. 2.Dept. of Mechanical EngineeringToyo UniversityKawagoe, SaitamaJapan

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