University of Hertfordshire

By the same authors

Human Perceptions of the Severity of Domestic Robot Errors

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Human Perceptions of the Severity of Domestic Robot Errors. / Rossi, Alessandra; Dautenhahn, Kerstin; Koay, Kheng Lee; Walters, Michael L.

Social Robotics - 9th International Conference, ICSR 2017, Proceedings. Vol. 10652 LNAI Springer Verlag, 2017. p. 647-656 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10652 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Rossi, A, Dautenhahn, K, Koay, KL & Walters, ML 2017, Human Perceptions of the Severity of Domestic Robot Errors. in Social Robotics - 9th International Conference, ICSR 2017, Proceedings. vol. 10652 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10652 LNAI, Springer Verlag, pp. 647-656, 9th International Conference on Social Robotics, ICSR 2017, Tsukuba, Japan, 22/11/17. https://doi.org/10.1007/978-3-319-70022-9_64

APA

Rossi, A., Dautenhahn, K., Koay, K. L., & Walters, M. L. (2017). Human Perceptions of the Severity of Domestic Robot Errors. In Social Robotics - 9th International Conference, ICSR 2017, Proceedings (Vol. 10652 LNAI, pp. 647-656). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10652 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-70022-9_64

Vancouver

Rossi A, Dautenhahn K, Koay KL, Walters ML. Human Perceptions of the Severity of Domestic Robot Errors. In Social Robotics - 9th International Conference, ICSR 2017, Proceedings. Vol. 10652 LNAI. Springer Verlag. 2017. p. 647-656. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-70022-9_64

Author

Rossi, Alessandra ; Dautenhahn, Kerstin ; Koay, Kheng Lee ; Walters, Michael L. / Human Perceptions of the Severity of Domestic Robot Errors. Social Robotics - 9th International Conference, ICSR 2017, Proceedings. Vol. 10652 LNAI Springer Verlag, 2017. pp. 647-656 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Bibtex

@inproceedings{0b8a97cbca4c488b8a9a5428a8b0cd4b,
title = "Human Perceptions of the Severity of Domestic Robot Errors",
abstract = "As robots increasingly take part in daily living activities, humans will have to interact with them in domestic and other human-oriented environments. We can expect that domestic robots will exhibit occasional mechanical, programming or functional errors, as occur with other electrical consumer devices. For example, these errors could include software errors, dropping objects due to gripper malfunctions, picking up the wrong object or showing faulty navigational skills due to unclear camera images or noisy laser scanner data respectively. It is therefore important for a domestic robot to have acceptable interactive behaviour when exhibiting and recovering from an error situation. As a first step, the current study investigated human users’ perceptions of the severity of various categories of potential errors that are likely to be exhibited by a domestic robot. We conducted a questionnaire-based study, where participants rated 20 different scenarios in which a domestic robot made an error. The potential errors were rated by participants by severity. Our findings indicate that people perceptions of the magnitude of the errors presented in the questionnaire were consistent. We did not find any significant differences in users’ ratings due to age and gender. We clearly identified scenarios that were rated by participants as having limited consequences (“small” errors) and that were rated as having severe consequences (“big” errors). Future work will use these two sets of consistently rated robot error scenarios as baseline scenarios to perform studies with repeated interactions investigating human perceptions of robot tasks and error severity.",
keywords = "Human-Robot Interaction, Robot companion, Social robotics",
author = "Alessandra Rossi and Kerstin Dautenhahn and Koay, {Kheng Lee} and Walters, {Michael L.}",
year = "2017",
month = "1",
day = "1",
doi = "10.1007/978-3-319-70022-9_64",
language = "English",
isbn = "9783319700212",
volume = "10652 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "647--656",
booktitle = "Social Robotics - 9th International Conference, ICSR 2017, Proceedings",
address = "Germany",

}

RIS

TY - GEN

T1 - Human Perceptions of the Severity of Domestic Robot Errors

AU - Rossi, Alessandra

AU - Dautenhahn, Kerstin

AU - Koay, Kheng Lee

AU - Walters, Michael L.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - As robots increasingly take part in daily living activities, humans will have to interact with them in domestic and other human-oriented environments. We can expect that domestic robots will exhibit occasional mechanical, programming or functional errors, as occur with other electrical consumer devices. For example, these errors could include software errors, dropping objects due to gripper malfunctions, picking up the wrong object or showing faulty navigational skills due to unclear camera images or noisy laser scanner data respectively. It is therefore important for a domestic robot to have acceptable interactive behaviour when exhibiting and recovering from an error situation. As a first step, the current study investigated human users’ perceptions of the severity of various categories of potential errors that are likely to be exhibited by a domestic robot. We conducted a questionnaire-based study, where participants rated 20 different scenarios in which a domestic robot made an error. The potential errors were rated by participants by severity. Our findings indicate that people perceptions of the magnitude of the errors presented in the questionnaire were consistent. We did not find any significant differences in users’ ratings due to age and gender. We clearly identified scenarios that were rated by participants as having limited consequences (“small” errors) and that were rated as having severe consequences (“big” errors). Future work will use these two sets of consistently rated robot error scenarios as baseline scenarios to perform studies with repeated interactions investigating human perceptions of robot tasks and error severity.

AB - As robots increasingly take part in daily living activities, humans will have to interact with them in domestic and other human-oriented environments. We can expect that domestic robots will exhibit occasional mechanical, programming or functional errors, as occur with other electrical consumer devices. For example, these errors could include software errors, dropping objects due to gripper malfunctions, picking up the wrong object or showing faulty navigational skills due to unclear camera images or noisy laser scanner data respectively. It is therefore important for a domestic robot to have acceptable interactive behaviour when exhibiting and recovering from an error situation. As a first step, the current study investigated human users’ perceptions of the severity of various categories of potential errors that are likely to be exhibited by a domestic robot. We conducted a questionnaire-based study, where participants rated 20 different scenarios in which a domestic robot made an error. The potential errors were rated by participants by severity. Our findings indicate that people perceptions of the magnitude of the errors presented in the questionnaire were consistent. We did not find any significant differences in users’ ratings due to age and gender. We clearly identified scenarios that were rated by participants as having limited consequences (“small” errors) and that were rated as having severe consequences (“big” errors). Future work will use these two sets of consistently rated robot error scenarios as baseline scenarios to perform studies with repeated interactions investigating human perceptions of robot tasks and error severity.

KW - Human-Robot Interaction

KW - Robot companion

KW - Social robotics

UR - http://www.scopus.com/inward/record.url?scp=85035764109&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-70022-9_64

DO - 10.1007/978-3-319-70022-9_64

M3 - Conference contribution

SN - 9783319700212

VL - 10652 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 647

EP - 656

BT - Social Robotics - 9th International Conference, ICSR 2017, Proceedings

PB - Springer Verlag

ER -