Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration

Kasper Hald; Matthias Rehm; Thomas B. Moeslund

doi:10.1109/RO-MAN46459.2019.8956335

Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration

Kasper Hald, Matthias Rehm, Thomas B. Moeslund

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

18 Citationer (Scopus)

Abstract

We propose a method of human-robot trust assessment in close-proximity human-robot collaboration involving body tracking for recognition of physical signs of apprehension. We tested this by performing skeleton tracking on 30 participant while they repeated a shared task with a Sawyer robot while reporting trust between tasks. We tested different robot velocity and environment conditions with an unannounced increase in velocity midway through to provoke a dip trust. Initial analysis show significant effect for the test conditions on participant movements and reported trust as well as linear correlations between tracked signs of apprehension and reported trust.

Originalsprog	Engelsk
Titel	28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN)
Forlag	IEEE Computer Society Press
Publikationsdato	2019
Artikelnummer	8956335
ISBN (Elektronisk)	978-1-7281-2622-7
DOI	https://doi.org/10.1109/RO-MAN46459.2019.8956335
Status	Udgivet - 2019
Begivenhed	The 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN): Ro-man2019 - New Delhi, Indien Varighed: 14 okt. 2019 → 18 nov. 2019 https://ro-man2019.org/

Konference

Konference	The 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
Land/Område	Indien
By	New Delhi
Periode	14/10/2019 → 18/11/2019
Internetadresse	https://ro-man2019.org/

Navn	IEEE RO-MAN proceedings
ISSN	1944-9445

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10.1109/RO-MAN46459.2019.8956335

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Drapebot: Collaborative Draping of Carbon Fiber Parts
Rehm, M. (PI (principal investigator)) & Hald, K. (PI (principal investigator))
Horizon Europe
01/01/2021 → 31/12/2024
Projekter: Projekt › Forskning

18 Citationer
1 Ph.d.-afhandling

Human-Robot Trust Assessment From Physical Apprehension Signals
Hald, K., 2021, Aalborg Universitetsforlag. 173 s.
Publikation: Ph.d.-afhandling

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title = "Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration",

abstract = "We propose a method of human-robot trust assessment in close-proximity human-robot collaboration involving body tracking for recognition of physical signs of apprehension. We tested this by performing skeleton tracking on 30 participant while they repeated a shared task with a Sawyer robot while reporting trust between tasks. We tested different robot velocity and environment conditions with an unannounced increase in velocity midway through to provoke a dip trust. Initial analysis show significant effect for the test conditions on participant movements and reported trust as well as linear correlations between tracked signs of apprehension and reported trust.",

keywords = "Human Robot Interaction, Human Robot Collaboration, human robot trust",

author = "Kasper Hald and Matthias Rehm and Moeslund, {Thomas B.}",

year = "2019",

doi = "10.1109/RO-MAN46459.2019.8956335",

language = "English",

series = "IEEE RO-MAN proceedings",

publisher = "IEEE Computer Society Press",

booktitle = "28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN)",

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note = "The 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) : Ro-man2019 ; Conference date: 14-10-2019 Through 18-11-2019",

url = "https://ro-man2019.org/",

}

Hald, K , Rehm, M & Moeslund, TB 2019, Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration. i 28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN)., 8956335, IEEE Computer Society Press, IEEE RO-MAN proceedings, The 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), New Delhi, Indien, 14/10/2019. https://doi.org/10.1109/RO-MAN46459.2019.8956335

Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration. / Hald, Kasper ; Rehm, Matthias ; Moeslund, Thomas B.
28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN). IEEE Computer Society Press, 2019. 8956335 (IEEE RO-MAN proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AU - Rehm, Matthias

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AB - We propose a method of human-robot trust assessment in close-proximity human-robot collaboration involving body tracking for recognition of physical signs of apprehension. We tested this by performing skeleton tracking on 30 participant while they repeated a shared task with a Sawyer robot while reporting trust between tasks. We tested different robot velocity and environment conditions with an unannounced increase in velocity midway through to provoke a dip trust. Initial analysis show significant effect for the test conditions on participant movements and reported trust as well as linear correlations between tracked signs of apprehension and reported trust.

KW - Human Robot Interaction

KW - Human Robot Collaboration

KW - human robot trust

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M3 - Article in proceeding

T3 - IEEE RO-MAN proceedings

BT - 28th IEEE International Conference on Robot and Human Interactive Communication (ROMAN)

PB - IEEE Computer Society Press

T2 - The 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

Y2 - 14 October 2019 through 18 November 2019

ER -

Proposing Human-Robot Trust Assessment Through Tracking Physical Apprehension Signals in Close-Proximity Human-Robot Collaboration

Abstract

Konference

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Drapebot: Collaborative Draping of Carbon Fiber Parts

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Human-Robot Trust Assessment From Physical Apprehension Signals

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