Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista

Mei Yii Lim; David Robb; Bruce Wilson; Helen Hastie

doi:10.1109/RO-MAN57019.2023.10309621

Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista

Mei Yii Lim^*, David Robb, Bruce Wilson, Helen Hastie

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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Abstract

Studying Human-Robot Interaction over time can provide insights into what really happens when a robot becomes part of people's everyday lives. "In the Wild" studies inform the design of social robots, such as for the service industry, to enable them to remain engaging and useful beyond the novelty effect and initial adoption. This paper presents an "In the Wild" experiment where we explored the evolution of interaction between users and a Robo-Barista. We show that perceived trust and prior attitudes are both important factors associated with the usefulness, adaptability and likeability of the Robo-Barista. A combination of interaction features and user attributes are used to predict user satisfaction. Qualitative insights illuminated users' Robo-Barista experience and contribute to a number of lessons learned for future long-term studies.

Original language	English
Title of host publication	32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
Publisher	IEEE
ISBN (Electronic)	9798350336702
DOIs	https://doi.org/10.1109/RO-MAN57019.2023.10309621
Publication status	Published - 13 Nov 2023
Event	32nd IEEE International Conference on Robot and Human Interactive Communication 2023 - Paradise Hotel, Busan, Korea, Republic of Duration: 28 Aug 2023 → 31 Aug 2023 Conference number: 32 https://ro-man2023.org/

Conference

Conference	32nd IEEE International Conference on Robot and Human Interactive Communication 2023
Abbreviated title	IEEE RO-MAN 2023
Country/Territory	Korea, Republic of
City	Busan
Period	28/08/23 → 31/08/23
Internet address	https://ro-man2023.org/

Keywords

robot barista
service robot
longitudinal study
conversational agent
human-robot interaction
user satisfaction
trust

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10.1109/RO-MAN57019.2023.10309621

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Accepted author manuscript, 392 KBLicence: CC BY

Cite this

@inproceedings{d28da33a2ba64c3dbc85aa8efdf42a8c,

title = "Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista",

abstract = "Studying Human-Robot Interaction over time can provide insights into what really happens when a robot becomes part of people's everyday lives. {"}In the Wild{"} studies inform the design of social robots, such as for the service industry, to enable them to remain engaging and useful beyond the novelty effect and initial adoption. This paper presents an {"}In the Wild{"} experiment where we explored the evolution of interaction between users and a Robo-Barista. We show that perceived trust and prior attitudes are both important factors associated with the usefulness, adaptability and likeability of the Robo-Barista. A combination of interaction features and user attributes are used to predict user satisfaction. Qualitative insights illuminated users' Robo-Barista experience and contribute to a number of lessons learned for future long-term studies.",

keywords = "robot barista, service robot, longitudinal study, conversational agent, human-robot interaction, user satisfaction, trust",

author = "Lim, {Mei Yii} and David Robb and Bruce Wilson and Helen Hastie",

note = "Funding information: This work was funded and supported by the UKRI Node on Trust (EP/V026682/1) and EPSRC CDT on Robotics and Autonomous Systems (EP/S023208/1).; 32nd IEEE International Conference on Robot and Human Interactive Communication 2023, IEEE RO-MAN 2023 ; Conference date: 28-08-2023 Through 31-08-2023",

year = "2023",

month = nov,

day = "13",

doi = "10.1109/RO-MAN57019.2023.10309621",

language = "English",

booktitle = "32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)",

publisher = "IEEE",

address = "United States",

url = "https://ro-man2023.org/",

}

Lim, MY, Robb, D , Wilson, B & Hastie, H 2023, Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista. in 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)., 10309621, IEEE, 32nd IEEE International Conference on Robot and Human Interactive Communication 2023, Busan, Korea, Republic of, 28/08/23. https://doi.org/10.1109/RO-MAN57019.2023.10309621

TY - GEN

T1 - Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista

AU - Lim, Mei Yii

AU - Robb, David

AU - Wilson, Bruce

AU - Hastie, Helen

N1 - Conference code: 32

PY - 2023/11/13

Y1 - 2023/11/13

N2 - Studying Human-Robot Interaction over time can provide insights into what really happens when a robot becomes part of people's everyday lives. "In the Wild" studies inform the design of social robots, such as for the service industry, to enable them to remain engaging and useful beyond the novelty effect and initial adoption. This paper presents an "In the Wild" experiment where we explored the evolution of interaction between users and a Robo-Barista. We show that perceived trust and prior attitudes are both important factors associated with the usefulness, adaptability and likeability of the Robo-Barista. A combination of interaction features and user attributes are used to predict user satisfaction. Qualitative insights illuminated users' Robo-Barista experience and contribute to a number of lessons learned for future long-term studies.

AB - Studying Human-Robot Interaction over time can provide insights into what really happens when a robot becomes part of people's everyday lives. "In the Wild" studies inform the design of social robots, such as for the service industry, to enable them to remain engaging and useful beyond the novelty effect and initial adoption. This paper presents an "In the Wild" experiment where we explored the evolution of interaction between users and a Robo-Barista. We show that perceived trust and prior attitudes are both important factors associated with the usefulness, adaptability and likeability of the Robo-Barista. A combination of interaction features and user attributes are used to predict user satisfaction. Qualitative insights illuminated users' Robo-Barista experience and contribute to a number of lessons learned for future long-term studies.

KW - robot barista

KW - service robot

KW - longitudinal study

KW - conversational agent

KW - human-robot interaction

KW - user satisfaction

KW - trust

U2 - 10.1109/RO-MAN57019.2023.10309621

DO - 10.1109/RO-MAN57019.2023.10309621

M3 - Conference contribution

BT - 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

PB - IEEE

T2 - 32nd IEEE International Conference on Robot and Human Interactive Communication 2023

Y2 - 28 August 2023 through 31 August 2023

ER -

Feeding the Coffee Habit: A Longitudinal Study of a Robo-Barista

Abstract

Conference

Keywords

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