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Learning to Acquire Autonomous Behavior
Cooperation by Humanoid Robots
Yutaka Inoue, Takahiro Tohge, and Hitoshi Iba
Department of Frontier Informatics, Graduate School of Frontier Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japaninoue@iba.k.u-tokyo.ac.jp
tohge@iba.k.u-tokyo.ac.jp
iba@iba.k.u-tokyo.ac.jp
Abstract. In this paper, we describe a cooperative transportation to a target position with two humanoid robots and introduce a machine learning approach to solving the problem. The difficulty of the task lies on the fact that each position shifts with the other’s while they are moving. Therefore, it is necessary to correct the position in a real-time manner. However, it is difficult to generate such an action in consideration of the physical formula. We empirically show how successful the humanoid robot HOAP-1’s cooperate with each other for the sake of the transportation as a result of Q-learning. Furthermore, we show a result of the experiment that transports an object cooperatively to a target position using those robots.
LNCS 3102, p. 590 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2004