I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration

Janis Stolzenwald; Walterio Mayol-Cuevas

doi:10.1109/IROS.2018.8594184

I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration

Janis Stolzenwald, Walterio Mayol-Cuevas

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

4 Citations (Scopus)

574 Downloads (Pure)

Abstract

This paper explores the estimation of user attention in the setting of a cooperative handheld robot — a robot designed to behave as a handheld tool but that has levels of task knowledge. We use a tool-mounted gaze tracking system, which, after modelling via a pilot study, we use as a proxy for estimating the attention of the user. This information is then used for cooperation with users in a task of selecting and engaging with objects on a dynamic screen. Via a video game setup, we test various degrees of robot autonomy from fully autonomous, where the robot knows what it has to do and acts, to no autonomy where the user is in full control of the task. Our results measure performance and subjective metrics and show how the attention model benefits the interaction and preference of users.

Original language	English
Title of host publication	2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)
Subtitle of host publication	Proceedings of a meeting held 1-5 October 2018, Madrid, Spain
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	3897-3904
Number of pages	8
ISBN (Electronic)	9781538680940
ISBN (Print)	9781538680933
DOIs	https://doi.org/10.1109/IROS.2018.8594184
Publication status	Published - Mar 2019

Publication series

Name	IEEE International Conference on Intelligent Robots and Systems
ISSN (Print)	2153-0858
ISSN (Electronic)	2153-0866

Access to Document

10.1109/IROS.2018.8594184

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Stolzenwald, J., & Mayol-Cuevas, W. (2019). I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018): Proceedings of a meeting held 1-5 October 2018, Madrid, Spain (pp. 3897-3904). Article 8594184 (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IROS.2018.8594184

Stolzenwald, Janis ; Mayol-Cuevas, Walterio. / I Can See Your Aim : Estimating User Attention from Gaze for Handheld Robot Collaboration. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018): Proceedings of a meeting held 1-5 October 2018, Madrid, Spain. Institute of Electrical and Electronics Engineers (IEEE), 2019. pp. 3897-3904 (IEEE International Conference on Intelligent Robots and Systems).

@inproceedings{05dc12223ad04e6a8d959f571cefa333,

title = "I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration",

abstract = "This paper explores the estimation of user attention in the setting of a cooperative handheld robot — a robot designed to behave as a handheld tool but that has levels of task knowledge. We use a tool-mounted gaze tracking system, which, after modelling via a pilot study, we use as a proxy for estimating the attention of the user. This information is then used for cooperation with users in a task of selecting and engaging with objects on a dynamic screen. Via a video game setup, we test various degrees of robot autonomy from fully autonomous, where the robot knows what it has to do and acts, to no autonomy where the user is in full control of the task. Our results measure performance and subjective metrics and show how the attention model benefits the interaction and preference of users.",

author = "Janis Stolzenwald and Walterio Mayol-Cuevas",

year = "2019",

month = mar,

doi = "10.1109/IROS.2018.8594184",

language = "English",

isbn = "9781538680933",

series = "IEEE International Conference on Intelligent Robots and Systems",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "3897--3904",

booktitle = "2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)",

address = "United States",

}

Stolzenwald, J & Mayol-Cuevas, W 2019, I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration. in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018): Proceedings of a meeting held 1-5 October 2018, Madrid, Spain., 8594184, IEEE International Conference on Intelligent Robots and Systems, Institute of Electrical and Electronics Engineers (IEEE), pp. 3897-3904. https://doi.org/10.1109/IROS.2018.8594184

I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration. / Stolzenwald, Janis; Mayol-Cuevas, Walterio.
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018): Proceedings of a meeting held 1-5 October 2018, Madrid, Spain. Institute of Electrical and Electronics Engineers (IEEE), 2019. p. 3897-3904 8594184 (IEEE International Conference on Intelligent Robots and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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N2 - This paper explores the estimation of user attention in the setting of a cooperative handheld robot — a robot designed to behave as a handheld tool but that has levels of task knowledge. We use a tool-mounted gaze tracking system, which, after modelling via a pilot study, we use as a proxy for estimating the attention of the user. This information is then used for cooperation with users in a task of selecting and engaging with objects on a dynamic screen. Via a video game setup, we test various degrees of robot autonomy from fully autonomous, where the robot knows what it has to do and acts, to no autonomy where the user is in full control of the task. Our results measure performance and subjective metrics and show how the attention model benefits the interaction and preference of users.

AB - This paper explores the estimation of user attention in the setting of a cooperative handheld robot — a robot designed to behave as a handheld tool but that has levels of task knowledge. We use a tool-mounted gaze tracking system, which, after modelling via a pilot study, we use as a proxy for estimating the attention of the user. This information is then used for cooperation with users in a task of selecting and engaging with objects on a dynamic screen. Via a video game setup, we test various degrees of robot autonomy from fully autonomous, where the robot knows what it has to do and acts, to no autonomy where the user is in full control of the task. Our results measure performance and subjective metrics and show how the attention model benefits the interaction and preference of users.

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DO - 10.1109/IROS.2018.8594184

M3 - Conference Contribution (Conference Proceeding)

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BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018)

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Stolzenwald J, Mayol-Cuevas W. I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018): Proceedings of a meeting held 1-5 October 2018, Madrid, Spain. Institute of Electrical and Electronics Engineers (IEEE). 2019. p. 3897-3904. 8594184. (IEEE International Conference on Intelligent Robots and Systems). Epub 2019 Jan 7. doi: 10.1109/IROS.2018.8594184

I Can See Your Aim: Estimating User Attention from Gaze for Handheld Robot Collaboration

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