| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2024-02-07 |
| タイトル |
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タイトル |
Environment-adaptive interaction primitives through visual context for human?robot motor skill learning |
| 言語 |
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言語 |
eng |
| キーワード |
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主題Scheme |
Other |
|
主題 |
Learning from demonstration |
| キーワード |
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主題Scheme |
Other |
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主題 |
Physical human?robot interaction |
| キーワード |
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主題Scheme |
Other |
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主題 |
Human?robot coordination |
| 資源タイプ |
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資源タイプ |
journal article |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Cui, Yunduan
Poon, James
Miro, Jaime Valls
Yamazaki, Kimitoshi
杉本, 謙二
松原, 崇充
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
In situations where robots need to closely co-operate with human partners, consideration of the task combined with partner observation maintains robustness when partner behavior is erratic or ambiguous. This paper documents our approach to capture human?robot interactive skills by combining their demonstrative data with additional environmental parameters automatically derived from observation of task context without the need for heuristic assignment, as an extension to overcome shortcomings of the interaction primitives framework. These parameters reduce the partner observation period required before suitable robot motion can commence, while also enabling success in cases where partner observation alone was inadequate for planning actions suited to the task. Validation in a collaborative object covering exercise with a humanoid robot demonstrate the robustness of our environment-adaptive interaction primitives, when augmented with parameters directly drawn from visual data of the task scene. |
| 書誌情報 |
en : Autonomous Robots
巻 43,
号 5,
p. 1225-1240,
発行日 2018-08-18
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| 出版者 |
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出版者 |
Springer |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
1573-7527 |
| 出版者版DOI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1007/s10514-018-9798-2 |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://link.springer.com/article/10.1007/s10514-018-9798-2 |
| 権利 |
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|
権利情報Resource |
http://creativecommons.org/licenses/by/4.0/ |
|
権利情報 |
c The Author(s) 2018 This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| 著者版フラグ |
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出版タイプ |
NA |
