Autonomous Learning of Ball Trapping in the Four-Legged Robot League

  • Hayato Kobayashi
  • Tsugutoyo Osaki
  • Eric Williams
  • Akira Ishino
  • Ayumi Shinohara
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4434)


This paper describes an autonomous learning method used with real robots in order to acquire ball trapping skills in the four-legged robot league. These skills involve stopping and controlling an oncoming ball and are essential to passing a ball to each other. We first prepare some training equipment and then experiment with only one robot. The robot can use our method to acquire these necessary skills on its own, much in the same way that a human practicing against a wall can learn the proper movements and actions of soccer on his/her own. We also experiment with two robots, and our findings suggest that robots communicating between each other can learn more rapidly than those without any communication.


Active Learner Trap Action Quadruped Robot Reinforcement Learning Algorithm Autonomous Learning 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Hayato Kobayashi
    • 1
  • Tsugutoyo Osaki
    • 2
  • Eric Williams
    • 2
  • Akira Ishino
    • 3
  • Ayumi Shinohara
    • 2
  1. 1.Department of Informatics, Kyushu UniversityJapan
  2. 2.Graduate School of Information Science, Tohoku UniversityJapan
  3. 3.Office for Information of University Evaluation, Kyushu UniversityJapan

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