NDLI: Consideration on robotic giant-swing motion generated by reinforcement learning

Content Provider	IEEE Xplore Digital Library
Author	Hara, M. Kawabe, N. Sakai, N. Huang, J. Bleuler, H. Yabuta, T.
Copyright Year	2009
Description	Author affiliation: Ecole Polytechnique Fédérale de Lausanne, 1015 Switzerland (Hara, M.; Bleuler, H.) \|\| Graduate School of Information Science and Technology, The University of Tokyo, 113-8656 Japan (Kawabe, N.) \|\| Dept. of Mechanical Engineering, Yokohama National University, 240-8501 Japan (Sakai, N.; Yabuta, T.) \|\| Dept. of Intelligent Mechanical Engineering, School of Engineering, Kinki University, Higashi-Hiroshima, 739-2116 Japan (Huang, J.)
Abstract	This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environment is available. Generally, it is widely said that this type of learning method is not appropriated to obtain dynamic motions because Markov property is not necessarily guaranteed during the dynamic task. However, in this study, we try to avoid this problem by embedding the dynamic information in the robotic state space; the applicability of the proposed method is considered using both the real robot and dynamic simulator. This paper, in particular, discusses how the robot with 5-DOF, in which the Q-Learning algorithm is implemented, acquires a giant-swing motion. Further, we describe the reward effects on the Q-Learning. Finally, this paper demonstrates that the application of the Q-Learning enable the robot to perform a very attractive giant-swing motion.
Starting Page	4206
Ending Page	4211
File Size	922832
Page Count	6
File Format	PDF
ISBN	9781424438037
DOI	10.1109/IROS.2009.5354270
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humanoid robots Learning systems Orbital robotics Intelligent robots Robot motion Supervised learning Mobile robots Human robot interaction Legged locomotion Unsupervised learning
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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