MISC

2020年5月

運動プリミティブを用いた強化学習による空気圧連続アームの投擲運動

日本機械学会ロボティクス・メカトロニクス講演会講演論文集(CD-ROM)
  • 森本亮太
  • ,
  • 西川鋭
  • ,
  • 新山龍馬
  • ,
  • 國吉康夫

2020
開始ページ
1P2
終了ページ
J05
記述言語
日本語
掲載種別
DOI
10.1299/jsmermd.2020.1P2-J05
出版者・発行元
一般社団法人 日本機械学会

<p>Previous research on reinforcement learning for continuum robot arms have been dealt with a relatively small number of active degrees of freedom and made experiments of simple tasks such as reaching. We aimed to learn to throw a ball by reinforcement learning in a pneumatically-controlled continuum robot arm that has nine actuators. We adopt Cost-regularized Kernel Regression (CrKR) which uses dynamic movement primitives (DMPs) which is one of the movement primitives. In the simulation, the continuum arm was able to learn how to throw a ball forward. We made the same experiment for our real continuum robot arm and found that the learning progressed in the experiment.</p>

リンク情報
DOI
https://doi.org/10.1299/jsmermd.2020.1P2-J05
J-GLOBAL
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=202002222832156415
CiNii Articles
http://ci.nii.ac.jp/naid/130007943713
ID情報
  • DOI : 10.1299/jsmermd.2020.1P2-J05
  • ISSN : 2424-3124
  • J-Global ID : 202002222832156415
  • CiNii Articles ID : 130007943713

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