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ID 14177
本文ファイル
著者
Ito, Koji
Morasso, Pietro
NDC
機械工学
抄録(英)
lmpedance control is one of the most effective controlmethods for the manipulators in contact with their environments.The characteristics of force and motion control, however, isdetermined by a desired impedance parameter of a manipulator'send-effector that should be carefully designed according to agiven task and an environment. The present paper proposesa new method to regulate the impedance parameter of theend-effector through learning of neural networks. Three kindsof the feed-forward networks are prepared corresponding toposition, velocity and force control loops of the end-effector beforelearning. First, the neural networks for position and velocitycontrol are trained using iterative learning of the manipulatorduring free movements. Then, the neural network for forcecontrol is trained for contact movements. During learning ofcontact movements, a virtual trajectory is also modified to reducecontrol error. The method can regulate not only stiffness andviscosity but also inertia and virtual trajectory of the end-effector.Computer simulations show that a smooth transition from freeto contact movements can be realized by regulating impedanceparameters before a contact.
掲載誌名
IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics,
26巻
2号
開始ページ
290
終了ページ
298
出版年月日
1996
出版者
IEEE
ISSN
1083-4419
言語
英語
NII資源タイプ
学術雑誌論文
広大資料タイプ
学術雑誌論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
Copyright (c) 1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
関連情報URL(IsVersionOf)
http://dx.doi.org/10.1109/3477.485879
部局名
工学研究科