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

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

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Abstrakt

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.

OriginalsprogEngelsk
Titel2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
ForlagIEEE
Publikationsdato8. aug. 2021
Sider110-116
ISBN (Elektronisk)9781665404921
DOI
StatusUdgivet - 8. aug. 2021
Begivenhed30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021 - Virtual, Vancouver, Canada
Varighed: 8. aug. 202112. aug. 2021

Konference

Konference30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021
Land/OmrådeCanada
ByVirtual, Vancouver
Periode08/08/202112/08/2021
NavnIEEE RO-MAN proceedings
ISSN1944-9445

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.

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