More Web Proxy on the site http://driver.im/

research-article

Robot gestures make difficult tasks easier: the impact of gestures on perceived workload and task performance

Authors:

Reinier Rothuis,

Jorge Gallego-Pérez,

Daphne E. Karreman,

Vanessa EversAuthors Info & Claims

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1459 - 1466

https://doi.org/10.1145/2556288.2557274

Published: 26 April 2014 Publication History

Abstract

Gestures are important non-verbal signals in human communication. Research with virtual agents and robots has started to add to the scientific knowledge about gestures but many questions with respect to the use of gestures in human-computer interaction are still open. This paper investigates the influence of robot gestures on the users' perceived workload and task performance (i.e. information recall) in a direction-giving task. We conducted a 2 x 2 (robot gestures vs. no robot gestures x easy vs. difficult task) experiment. The results indicate that robot gestures increased user performance and decreased perceived workload in the difficult task but not in the easy task. Thus, robot gestures are a promising means to improve human-robot interaction particularly in challenging tasks.

References

[1]

Bergmann, K., Eyssel, F. A., and Kopp, S. A second chance to make a first impression' how appearance and nonverbal behavior affect perceived warmth and competence of virtual agents over time. M. Walker, M. Neff, A. Paiva, and Y. Nakano, Eds., Proceedings of the 12th International Conference on Intelligent Virtual Agents, Springer (2012), 126--138.

Digital Library

[2]

Bergmann, K., Kahl, S., and Kopp, S. Modeling the semantic coordination of speech and gesture under cognitive and linguistic constraints. In Intelligent Virtual Agents, R. Aylett, B. Krenn, C. Pelachaud, and H. Shimodaira, Eds., vol. 8108 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013, 203--216.

[3]

Breazeal, C., Kidd, C., Thomaz, A., Hoffman, G., and Berlin, M. Effects of nonverbal communication on efficiency and robustness in human-robot teamwork. In Intelligent Robots and Systems, 2005. (IROS 2005). 2005 IEEE/RSJ International Conference on (2005), 708--713.

[4]

Buisine, S., Abrilian, S., and Martin, J.-C. From brows to trust. Kluwer Academic Publishers, Norwell, MA, USA, 2004, ch. Evaluation of multimodal behaviour of embodied agents, 217--238.

Digital Library

[5]

Cassell, J. Embodied conversational agents. MIT Press, Cambridge, MA, USA, 2000, ch. Nudge nudge wink wink: elements of face-to-face conversation for embodied conversational agents, 1--27.

Digital Library

[6]

Chidambaram, V., Chiang, Y.-H., and Mutlu, B. Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues. In Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction, HRI '12, ACM (New York, NY, USA, 2012), 293--300.

Digital Library

[7]

Field, A. Discovering statistics using SPSS. Sage publications, 2009.

[8]

Fox, M. L., Dwyer, D. J., and Ganster, D. C. Effects of stressful job demands and control on physiological and attitudinal outcomes in a hospital setting. Academy of Management Journal 36, 2 (1993), 289--318.

[9]

Goldin-Meadow, S. Hearing Gesture: How Our Hands Help Us Think. Belknap Press of Harvard University Press, 2005.

[10]

Gu, E., and Badler, N. I. Visual attention and eye gaze during multiparty conversations with distractions. In IVA, J. Gratch, M. Young, R. Aylett, D. Ballin, and P. Olivier, Eds., vol. 4133 of Lecture Notes in Computer Science, Springer (2006), 193--204.

Digital Library

[11]

Häring, M., Eichberg, J., and André, E. Studies on grounding with gaze and pointing gestures in human-robot-interaction. In Social Robotics, S. Ge, O. Khatib, J.-J. Cabibihan, R. Simmons, and M.-A. Williams, Eds., vol. 7621 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012, 378--387.

Digital Library

[12]

Hart, S., and Staveland, L. Development of nasa-tlx (task load index): Results of empirical and theoretical research. In Human mental workload, P. A. Hancock and N. Meshkati (Eds.), Amsterdam: Elsevier (1988), 139--183.

[13]

Hart, S. G. Nasa-task load index (nasa-tlx); 20 years later. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 50, 9 (2006), 904--908.

[14]

Hato, Y., Satake, S., Kanda, T., Imai, M., and Hagita, N. Pointing to space: modeling of deictic interaction referring to regions. In Proceedings of the Conference on Human-Robot Interaction, P. J. Hinds, H. Ishiguro, T. Kanda, and P. H. K. Jr., Eds., ACM (2010), 301--308.

Digital Library

[15]

Ilies, R., Dimotakis, N., and De Pater, I. E. Psychological and physiological reactions to high workloads: Implications for well-being. Personnel Psychology 63, 2 (2010), 407--436.

[16]

Iverson, J. M., Capirci, P., Longobardi, E., and Caselli, M. C. Gesturing in mother-child interaction. Cognitive Development 14 (1999), 57--75.

[17]

Kanda, T., Shiomi, M., Miyashita, Z., Ishiguro, H., and Hagita, N. A communication robot in a shopping mall. Robotics, IEEE Transactions on 26, 5 (2010), 897--913.

Digital Library

[18]

Kendon, A. Gesture and speech: How they interact. In Nonverbal Interaction (Sage Annual Reviews of Communication, Volume 11) J. Wiemann and R. Harrison, Eds. Sage Publications, Beverly Hills, California, 1983, 13--46.

[19]

Kendon, A. Gesture - Visible Action as Utterance. Cambridge University Press, Cambridge, 2004.

[20]

Kipp, M., Neff, M., Kipp, K. H., and Albrecht, I. Towards natural gesture synthesis: Evaluating gesture units in a data-driven approach to gesture synthesis. In Proceedings of the 7th international conference on Intelligent Virtual Agents, IVA '07, Springer-Verlag (Berlin, Heidelberg, 2007), 15--28.

Digital Library

[21]

Kita, S. Pointing: Where Language, Culture, and Cognition Meet. PSYCHOLOGY Press, 2003.

[22]

McNeil, N., Alibali, M., and Evans, J. The role of gesture in children's comprehension of spoken language: now they need it, now they don't. Journal of Nonverbal Behavior 24, 2 (2000), 131--150.

[23]

McNeill, D. Hand and Mind: What Gestures Reveal about Thought. University of Chicago Press, Chicago, 1992.

[24]

Miller, G. A. The magical number seven, plus or minus two: Some limits on our capacity for processing information. The Psychological Review 63, 2 (March 1956), 81--97.

[25]

Ng-Thow-Hing, V., Luo, P., and Okita, S. Y. Synchronized gesture and speech production for humanoid robots. In IROS, IEEE (2010), 4617--4624.

[26]

Okuno, Y., Kanda, T., Imai, M., Ishiguro, H., and Hagita, N. Providing route directions: design of robot's utterance, gesture, and timing. In Proceedings of the 4th ACM/IEEE international conference on Human robot interaction, HRI '09, ACM (New York, NY, USA, 2009), 53--60.

Digital Library

[27]

Pelachaud, C. Studies on gesture expressivity for a virtual agent. Speech Commun. 51, 7 (July 2009), 630--639.

Digital Library

[28]

Salem, M., Eyssel, F., Rohlfing, K., Kopp, S., and Joublin, F. To err is human(-like): Effects of robot gesture on perceived anthropomorphism and likability. International Journal of Social Robotics 5, 3 (2013), 313--323.

[29]

Steinfeld, A., Fong, T., Kaber, D., Lewis, M., Scholtz, J., Schultz, A., and Goodrich, M. Common metrics for human-robot interaction. In Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction, HRI '06, ACM (New York, NY, USA, 2006), 33--40.

Digital Library

[30]

Vitense, H. S., Jacko, J. A., and Emery, V. K. Multimodal feedback: an assessment of performance and mental workload. Ergonomics 46, 1--3 (2003), 68--87. 12554399.

[31]

Yoshiike, Y., Silva, P. R. S. D., and Okada, M. Mawari: A social interface to reduce the workload of the conversation. In ICSR, B. Mutlu, C. Bartneck, J. Ham, V. Evers, and T. Kanda, Eds., vol. 7072 of Lecture Notes in Computer Science, Springer (2011), 11--20.

Digital Library

Cited By

Liu TZhao HLiu YWang XPeng Z(2024)ComPeer: A Generative Conversational Agent for Proactive Peer SupportProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676430(1-22)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676430
Kaushik RSimmons R(2024)Effects of Feedback Styles on Performance and Preference for an Exercise Coach2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)10.1109/RO-MAN60168.2024.10731249(1516-1523)Online publication date: 26-Aug-2024
https://doi.org/10.1109/RO-MAN60168.2024.10731249
Oralbayeva NAly ASandygulova ABelpaeme T(2023)Data-Driven Communicative Behaviour Generation: A SurveyACM Transactions on Human-Robot Interaction10.1145/3609235Online publication date: 16-Aug-2023
https://dl.acm.org/doi/10.1145/3609235
Show More Cited By

Index Terms

Robot gestures make difficult tasks easier: the impact of gestures on perceived workload and task performance
1. Human-centered computing

Recommendations

Cooperative gestures: effective signaling for humanoid robots
HRI '10: Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction

Cooperative gestures are a key aspect of human-human pro-social interaction. Thus, it is reasonable to expect that endowing humanoid robots with the ability to use such gestures when interacting with humans would be useful. However, while people are ...
Effects of Predictive Robot Eyes on Trust and Task Performance in an Industrial Cooperation Task
HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction

Industrial cobots can perform variable action sequences. For human-robot interaction (HRI) this can have detrimental effects, as the robot's actions can be difficult to predict. In human interaction, eye gaze intuitively directs attention and ...
Analysis of natural gestures for controlling robot teams on multi-touch tabletop surfaces
ITS '09: Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces

Multi-touch technologies hold much promise for the command and control of mobile robot teams. To improve the ease of learning and usability of these interfaces, we conducted an experiment to determine the gestures that people would naturally use, rather ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI '14: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

April 2014

4206 pages

ISBN:9781450324731

DOI:10.1145/2556288

General Chairs:
Matt Jones
Swansea University, Wales, UK
,
Philippe Palanque
Université Paul Sabatier, France
,
Program Chairs:
Albrecht Schmidt
University of Stuttgart, Germany
,
Tovi Grossman
Autodesk Research, Canada

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

CHI '14

Sponsor:

SIGCHI

CHI '14: CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2014

Ontario, Toronto, Canada

Acceptance Rates

CHI '14 Paper Acceptance Rate 465 of 2,043 submissions, 23%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

37
Total Citations
View Citations
709
Total Downloads

Downloads (Last 12 months)63
Downloads (Last 6 weeks)8

Reflects downloads up to 04 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Liu TZhao HLiu YWang XPeng Z(2024)ComPeer: A Generative Conversational Agent for Proactive Peer SupportProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676430(1-22)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676430
Kaushik RSimmons R(2024)Effects of Feedback Styles on Performance and Preference for an Exercise Coach2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)10.1109/RO-MAN60168.2024.10731249(1516-1523)Online publication date: 26-Aug-2024
https://doi.org/10.1109/RO-MAN60168.2024.10731249
Oralbayeva NAly ASandygulova ABelpaeme T(2023)Data-Driven Communicative Behaviour Generation: A SurveyACM Transactions on Human-Robot Interaction10.1145/3609235Online publication date: 16-Aug-2023
https://dl.acm.org/doi/10.1145/3609235
Urakami JSeaborn K(2023)Nonverbal Cues in Human–Robot Interaction: A Communication Studies PerspectiveACM Transactions on Human-Robot Interaction10.1145/357016912:2(1-21)Online publication date: 15-Mar-2023
https://dl.acm.org/doi/10.1145/3570169
Hordemann GQuek FPowell L(2023)Reaching Across the Communication Gap: Evaluating How Augmented Reality Shared Gestural Spaces Impact Gesture and Language Usage2023 IEEE Frontiers in Education Conference (FIE)10.1109/FIE58773.2023.10343016(1-6)Online publication date: 18-Oct-2023
https://doi.org/10.1109/FIE58773.2023.10343016
Chien SChen CChan Y(2023)The Impacts of Social Humanoid Robot’s Nonverbal Communication on Perceived Personality TraitsInternational Journal of Human–Computer Interaction10.1080/10447318.2023.2295696(1-13)Online publication date: 27-Dec-2023
https://doi.org/10.1080/10447318.2023.2295696
Song SLuo YRonca VBorghini GSagha HRick VMertens AGunes H(2023)Deep Learning-Based Assessment of Facial Periodic Affect in Work-Like SettingsComputer Vision – ECCV 2022 Workshops10.1007/978-3-031-25072-9_20(307-322)Online publication date: 18-Feb-2023
https://doi.org/10.1007/978-3-031-25072-9_20
de Wit JVogt PKrahmer E(2022)The Design and Observed Effects of Robot-performed Manual Gestures: A Systematic ReviewACM Transactions on Human-Robot Interaction10.1145/354953012:1(1-62)Online publication date: 19-Jul-2022
https://dl.acm.org/doi/10.1145/3549530
Kaushik RSimmons R(2022)Affective Robot Behavior Improves Learning in a Sorting Game2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)10.1109/RO-MAN53752.2022.9900654(436-441)Online publication date: 29-Aug-2022
https://doi.org/10.1109/RO-MAN53752.2022.9900654
Filipe LPeres RMarques FBarata J(2022)Gesture-Based Feedback in Human-Robot Interaction for Object ManipulationTechnological Innovation for Digitalization and Virtualization10.1007/978-3-031-07520-9_12(122-132)Online publication date: 21-Jun-2022
https://doi.org/10.1007/978-3-031-07520-9_12
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents