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

Kei Senda | Zendy; Takayuki Kondo | Zendy; Yoshimitsu Iwasaki | Zendy; Shinji Fujii | Zendy; Naofumi FUJIWARA | Zendy; Naoki Suganuma | Zendy

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

Author(s) -

Kei Senda,

Takayuki Kondo,

Yoshimitsu Iwasaki,

Shinji Fujii,

Naofumi FUJIWARA,

Naoki Suganuma

Publication year - 2008

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2008.p0350

Subject(s) - reinforcement learning , robot , computer science , controller (irrigation) , artificial intelligence , control engineering , engineering , biology , agronomy

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.

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