JRM Vol.20 No.3 pp. 350-357
doi: 10.20965/jrm.2008.p0350


Hardware and Numerical Experiments of Autonomous Robust Skill Generation Using Reinforcement Learning

Kei Senda, Takayuki Kondo, Yoshimitsu Iwasaki, Shinji Fujii,
Naofumi Fujiwara, and Naoki Suganuma

Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan

September 29, 2007
February 5, 2008
June 20, 2008
skill generation, reinforcement learning, space robot, robustness, autonomy
It is difficult for robots to achieve tasks contacting environment due to error between the controller models and the real environment. To solve this problem, we propose having a robot autonomously obtains proficient robust skills against model error. Numerical simulation and experiments using an autonomous space robot demonstrate the feasibility of our proposal in the real environment.
Cite this article as:
K. Senda, T. Kondo, Y. Iwasaki, S. Fujii, N. Fujiwara, and N. Suganuma, “Hardware and Numerical Experiments of Autonomous Robust Skill Generation Using Reinforcement Learning,” J. Robot. Mechatron., Vol.20 No.3, pp. 350-357, 2008.
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