Enabling robots to adhere to social norms by detecting F-formations

Avgi Kollakidou; Lakshadeep Naik; Oskar Palinko; Leon Bodenhagen

doi:10.1109/RO-MAN50785.2021.9515484

Enabling robots to adhere to social norms by detecting F-formations

Avgi Kollakidou^*, Lakshadeep Naik, Oskar Palinko, Leon Bodenhagen

^*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

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Abstract

Robot navigation in environments shared with humans should take into account social structures and interactions. The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups (FSCS), utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.

Originalsprog	Engelsk
Titel	2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
Forlag	IEEE
Publikationsdato	8. aug. 2021
Sider	110-116
ISBN (Elektronisk)	9781665404921
DOI	https://doi.org/10.1109/RO-MAN50785.2021.9515484
Status	Udgivet - 8. aug. 2021
Begivenhed	30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021 - Virtual, Vancouver, Canada Varighed: 8. aug. 2021 → 12. aug. 2021

Konference

Konference	30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
Land/Område	Canada
By	Virtual, Vancouver
Periode	08/08/2021 → 12/08/2021

Navn	IEEE RO-MAN proceedings
ISSN	1944-9445

Bibliografisk note

Funding Information:
ACKNOWLEDGMENT This research was supported by the project Health-CAT, funded by the European Fund for regional development.

Publisher Copyright:
© 2021 IEEE.

Dokumenter og links

10.1109/RO-MAN50785.2021.9515484

Open Access VersionAccepteret manuskript, 536 KB

Citationsformater

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title = "Enabling robots to adhere to social norms by detecting F-formations",

abstract = "Robot navigation in environments shared with humans should take into account social structures and interactions. The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups (FSCS), utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.",

author = "Avgi Kollakidou and Lakshadeep Naik and Oskar Palinko and Leon Bodenhagen",

note = "Funding Information: ACKNOWLEDGMENT This research was supported by the project Health-CAT, funded by the European Fund for regional development. Publisher Copyright: {\textcopyright} 2021 IEEE.; 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021 ; Conference date: 08-08-2021 Through 12-08-2021",

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Kollakidou, A , Naik, L , Palinko, O & Bodenhagen, L 2021, Enabling robots to adhere to social norms by detecting F-formations. i 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021. IEEE, IEEE RO-MAN proceedings, s. 110-116, 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021, Virtual, Vancouver, Canada, 08/08/2021. https://doi.org/10.1109/RO-MAN50785.2021.9515484

Enabling robots to adhere to social norms by detecting F-formations. / Kollakidou, Avgi ; Naik, Lakshadeep ; Palinko, Oskar et al.
2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021. IEEE, 2021. s. 110-116 (IEEE RO-MAN proceedings).

Publikation: Kapitel i bog/rapport/konference-proceeding › Konferencebidrag i proceedings › Forskning › peer review

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AU - Palinko, Oskar

AU - Bodenhagen, Leon

PY - 2021/8/8

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N2 - Robot navigation in environments shared with humans should take into account social structures and interactions. The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups (FSCS), utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.

AB - Robot navigation in environments shared with humans should take into account social structures and interactions. The identification of social groups has been a challenge for robotics as it encompasses a number of disciplines. We propose a hierarchical clustering method for grouping individuals into free standing conversational groups (FSCS), utilising their position and orientation. The proposed method is evaluated on the SALSA dataset with achieved F1 score of 0.94. The algorithm is also evaluated for scalability and implemented on a mobile robot attempting to detect social groups and engage in interaction.

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DO - 10.1109/RO-MAN50785.2021.9515484

M3 - Article in proceedings

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ER -

Enabling robots to adhere to social norms by detecting F-formations

Abstract

Konference

Bibliografisk note

Dokumenter og links

Fingeraftryk

Citationsformater