| アイテムタイプ |
itemtype_ver1(1) |
| 公開日 |
2025-05-15 |
| タイトル |
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|
タイトル |
Inducibility Analysis of Pedestrian's Interactive Behavior |
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言語 |
en |
| 著者 |
Sugiura, Kentaro
Okuda, Hiroyuki
Aoki, Mizuho
Uchida, Kazuma
Suzuki, Tatsuya
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| アクセス権 |
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|
アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 権利 |
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|
権利情報 |
“© 2025 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.” |
|
言語 |
en |
| 内容記述 |
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|
内容記述タイプ |
Abstract |
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内容記述 |
As the application fields of Autonomous Mobile Robots (AMRs) expand, stress-free interaction with people around them becomes more important. AMRs are highly required to interact with pedestrians like human-human interaction. This paper proposes a new measure, ’Inducibility,’ expressing how AMR’s behavior can induce (control) the other pedestrian’s behavior. In particular, this paper discusses two kinds of inducibility measures: one is based on the sensitivity of decision-making, and the other one is based on the controllability gramian for the state space model of the interactive behavior. Finally, the validity of these two measures is evaluated based on data on interaction behaviors, and typical applications of these measures are discussed. |
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言語 |
en |
| 出版者 |
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出版者 |
IEEE |
|
言語 |
en |
| 言語 |
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|
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 |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| 関連情報 |
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|
関連タイプ |
isVersionOf |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.1109/SII59315.2025.10870962 |
| 収録物識別子 |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2474-2325 |
| 書誌情報 |
en : 2025 IEEE/SICE International Symposium on System Integration, SII 2025
p. 1-7,
発行日 2025-01
|
Sugiura_SII2025_camera_ready.pdf (2.1 MB)
