WEKO3
アイテム
Bayesian Nonparametric Learning of Cloth Models for Real-Time State Estimation
http://hdl.handle.net/10228/00007729
http://hdl.handle.net/10228/00007729db09ee2d-5513-4fc0-8a09-d0048b540bf1
| 名前 / ファイル | ライセンス | アクション |
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10302310.pdf (3.2 MB)
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| アイテムタイプ | 学術雑誌論文 = Journal Article(1) | |||||||||||||
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| 公開日 | 2020-05-11 | |||||||||||||
| 資源タイプ | ||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||
| 資源タイプ | journal article | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | Bayesian Nonparametric Learning of Cloth Models for Real-Time State Estimation | |||||||||||||
| 言語 | en | |||||||||||||
| その他のタイトル | ||||||||||||||
| その他のタイトル | Bayesian Nonparametric Learning of Cloth Models for Real-time State Estimation | |||||||||||||
| 言語 | en | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| 著者 |
Koganti, Nishanth
× Koganti, Nishanth× Tamei, Tomoya× Ikeda, Kazushi× 柴田, 智広
WEKO
27592
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||
| 内容記述 | Robotic solutions to clothing assistance can significantly improve quality of life for the elderly and disabled. Real-time estimation of the human-cloth relationship is crucial for efficient learning of motor skills for robotic clothing assistance. The major challenge involved is cloth-state estimation due to inherent nonrigidity and occlusion. In this study, we present a novel framework for real-time estimation of the cloth state using a low-cost depth sensor, making it suitable for a feasible social implementation. The framework relies on the hypothesis that clothing articles are constrained to a low-dimensional latent manifold during clothing tasks. We propose the use of manifold relevance determination (MRD) to learn an offline cloth model that can be used to perform informed cloth-state estimation in real time. The cloth model is trained using observations from a motion capture system and depth sensor. MRD provides a principled probabilistic framework for inferring the accurate motion-capture state when only the noisy depth sensor feature state is available in real time. The experimental results demonstrate that our framework is capable of learning consistent task-specific latent features using few data samples and has the ability to generalize to unseen environmental settings. We further present several factors that affect the predictive performance of the learned cloth-state model. | |||||||||||||
| 書誌情報 |
IEEE Transactions on Robotics 巻 33, 号 4, p. 916-931, 発行日 2017-05-17 |
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| 出版者 | IEEE | |||||||||||||
| DOI | ||||||||||||||
| 関連タイプ | isVersionOf | |||||||||||||
| 識別子タイプ | DOI | |||||||||||||
| 関連識別子 | https://doi.org/10.1109/TRO.2017.2691721 | |||||||||||||
| NCID | ||||||||||||||
| 収録物識別子タイプ | NCID | |||||||||||||
| 収録物識別子 | AA1196840X | |||||||||||||
| ISSN | ||||||||||||||
| 収録物識別子タイプ | PISSN | |||||||||||||
| 収録物識別子 | 1552-3098 | |||||||||||||
| ISSN | ||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||
| 収録物識別子 | 1941-0468 | |||||||||||||
| 著作権関連情報 | ||||||||||||||
| 権利情報 | Copyright (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | Cloth-state estimation | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | learning and adaptive systems | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | personal robots | |||||||||||||
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| 主題Scheme | Other | |||||||||||||
| 主題 | robotic clothing assistance | |||||||||||||
| キーワード | ||||||||||||||
| 主題Scheme | Other | |||||||||||||
| 主題 | visual tracking | |||||||||||||
| 出版タイプ | ||||||||||||||
| 出版タイプ | AM | |||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||||
| 査読の有無 | ||||||||||||||
| 値 | yes | |||||||||||||
| 研究者情報 | ||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/100000703_ja.html | |||||||||||||
| 論文ID（連携） | ||||||||||||||
| 値 | 10302310 | |||||||||||||
| 連携ID | ||||||||||||||
| 値 | 8237 | |||||||||||||
