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  1. B200 工学部/工学研究科
  2. B200e 会議資料
  3. 国際会議

A framework for optimal gait generation via learning optimal control using virtual constraint

http://hdl.handle.net/2237/12079
eebf6472-c5e2-4a56-b48f-54a66611ce68
名前 / ファイル ライセンス アクション
iros08.pdf iros08.pdf (1.2 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2009-08-25
タイトル
タイトル A framework for optimal gait generation via learning optimal control using virtual constraint
著者 Satoh, Satoshi

× Satoh, Satoshi

WEKO 31084

Satoh, Satoshi

Search repository
Fujimoto, Kenji

× Fujimoto, Kenji

WEKO 31085

Fujimoto, Kenji

Search repository
Hyon, Sang-Ho

× Hyon, Sang-Ho

WEKO 31086

Hyon, Sang-Ho

Search repository
権利
権利情報 Copyright © 2008 IEEE. Reprinted from IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008. IROS 2008. p.3426-3432.
This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or 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 must be obtained from the IEEE by writing to pubs-permissions@ieee.org.
抄録
内容記述 This paper proposes an optimal gait generation framework using virtual constraint and learning optimal control. In this method, firstly, we add a constraint by a virtual potential energy to prevent the robot from falling. Secondly, we execute iterative learning control (ILC) to generate an optimal feedforward input. Thirdly, we execute iterative feedback tuning (IFT) to mitigate the strength of the virtual constraint
automatically according to the progress of learning control. Consequently, it is expected to generate an optimal gait without constraint eventually. Although existing ILC frameworks require a lot of experimental data under the same initial condition, the proposed method does not need to repeat experiments under the same initial condition because the virtual constraint restricts the motion of the robot to a symmetric
trajectory. Furthermore, it does not require the precise knowledge of the plant system. Finally, some numerical simulations demonstrate the effectiveness of the proposed method.
内容記述タイプ Abstract
出版者
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
書誌情報 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2008)

p. 3426-3432, 発行日 2008-09
フォーマット
application/pdf
著者版フラグ
値 author
URI
識別子 http://dx.doi.org/10.1109/IROS.2008.465086
識別子タイプ DOI
URI
識別子 http://hdl.handle.net/2237/12079
識別子タイプ HDL
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