skip to main content
10.1145/1877826.1877837acmconferencesArticle/Chapter ViewAbstractPublication Pagesicmi-mlmiConference Proceedingsconference-collections
research-article

Interpretation of emotional body language displayed by robots

Published: 29 October 2010 Publication History

Abstract

In order for robots to be socially accepted and generate empathy they must display emotions. For robots such as Nao, body language is the best medium available, as they do not have the ability to display facial expressions. Displaying emotional body language that can be interpreted whilst interacting with the robot should greatly improve its acceptance.
This research investigates the creation of an "Affect Space" [1] for the generation of emotional body language that could be displayed by robots. An Affect Space is generated by "blending" (i.e. interpolating between) different emotional expressions to create new ones. An Affect Space for body language based on the Circumplex Model of emotions [2] has been created.
The experiment reported in this paper investigated the perception of specific key poses from the Affect Space. The results suggest that this Affect Space for body expressions can be used to improve the expressiveness of humanoid robots.
In addition, early results of a pilot study are described. It revealed that the context helps human subjects improve their recognition rate during a human-robot imitation game, and in turn this recognition leads to better outcome of the interactions.

References

[1]
Breazal, C., Designing sociable robots. Intelligent Robotics & Autonomous Agents. 2002: MIT press.
[2]
Russell, J.A., A circumplex model of affect. Journal of Personality and Social Psychology, 1980. 39: p. 1161--1178.
[3]
Aldebaran, http://www.aldebaran-robotics.com/. 2010.
[4]
Beck, A., Canamero, L., Bard, K., Toward an affect space for robots to display body language. In proceedings of the International Symposium Re-thinking interaction with robots (Ro-Man 2010).
[5]
M. Gillies, et al., "Responsive listening behavior, "Computer animation and virtual worlds, vol. 19, pp. 579--589, 2008.
[6]
Saerbeck, M. and Bartneck, C. Perception of affect elicited by robot motion, in Human-Robot Interaction (HRI2010), ACM/IEE, Editor. 2010, ACM/IEE: Osaka. p. 53--60.
[7]
Andry, P., Gaussier, P., Moga, S., Banquet, J.P. and Nadel, J. Learning and communication via imitation: an autonomous robot perspective. In Transactions on Systems, Man, and Cybernetics, vol 31, number 5, pp 431--442, 2001.
[8]
Andry, P., Garnault, N. and Gaussier, P. Using the interaction rhythm to build an internal reinforcement signal: a tool for intuitive HRI, in Proceedings of the Ninth International Conference on Epigenetic Robotics 2009.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
AFFINE '10: Proceedings of the 3rd international workshop on Affective interaction in natural environments
October 2010
106 pages
ISBN:9781450301701
DOI:10.1145/1877826
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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 October 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. emotional body language
  2. human robot interactions

Qualifiers

  • Research-article

Conference

MM '10
Sponsor:
MM '10: ACM Multimedia Conference
October 29, 2010
Firenze, Italy

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)28
  • Downloads (Last 6 weeks)2
Reflects downloads up to 28 Dec 2024

Other Metrics

Citations

Cited By

View all

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media