電気学会論文誌C(電子・情報・システム部門誌)
Online ISSN : 1348-8155
Print ISSN : 0385-4221
<知能,ロボティクス>
多自由度マニピュレータによる関節負荷に基づく作業空間の学習
原田 篤鈴木 健嗣
著者情報
ジャーナル 認証あり

137 巻 (2017) 12 号 p. 1659-1668

詳細
PDFをダウンロード (7934K) 発行機関連絡先
抄録

This paper describes a novel method of probabilistic self-modeling based on learning of operating space from exploratory actions of a multi-DOF manipulator, which is designed for mounting it onto the wheelchair. The developed anthropomorphic multi-DOF manipulator is able to learn both of the operating range in each joint and the probabilistic operating space based on Gaussian Mixture Model and Variational Bayesian learning algorithm. We introduce an acquisition method of the operating space by using the historical data of irregular overload, which is detected by using analogue current signals measured by solely internal sensor of joint motors. In addition, online behavior learning with a simple probabilistic path planning is also presented based on the obtained probabilistic operating space. We will conduct several experiments with a real multi-DOF manipulator arm. After the basic characteristics of the obtained operating space are shown, the performance of interaction with different situations such as different load given to the arm and obstacles placed in the surrounding environment will also be demonstrated.

著者関連情報
© 2017 電気学会
前の記事 次の記事

閲覧履歴
ジャーナルのニュースとお知らせ
  • 【電気学会会員の方】購読している論文誌を無料でご覧いただけます(会員ご本人のみの個人としての利用に限ります)。購読者番号欄にMyページへのログインIDを,パスワード欄に生年月日8ケタ(西暦,半角数字。例:19800303)を入力して下さい。
ダウンロード
  • 論文(PDF)の閲覧方法はこちら
    閲覧方法 (389.7K)
関連情報

J-STAGEがリニューアルされました!  https://www.jstage.jst.go.jp/browse/-char/ja/

feedback
Top