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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access April 27, 2011

Non-Facial and Non-Verbal Affective Expression for Appearance-Constrained Robots Used in Victim Management*

  • Cindy L. Bethel EMAIL logo and Robin R. Murphy

Abstract

Non-facial and non-verbal methods of affective expression are essential for social interaction in appearance-constrained robots such as those used in search and rescue, law enforcement, and military applications. This research identified five main methods of non-facial and non-verbal affective expression (body movements, postures, orientation, color, and sound). Based on an extensive review of literature, prescriptive design recommendations were developed for the appropriate non-facial and non-verbal affective expression methods for three proximity zones of interest (intimate, personal, and social). These design recommendations serve as guidelines to add retroactively affective expression through software with minimal or no physical modification to a robot. A large-scale, complex human-robot interaction study was conducted to validate these design recommendations using 128 participants and four methods of evaluation. The study was conducted in a high-fidelity, confined-space simulated disaster site with all robot interactions performed in the dark. Statistically significant results indicated that participants felt the robots that exhibited affective expressions were more calming, friendly, and attentive, which improved the social human-robot interactions.


*This material is based upon work supported by the National Science Foundation under Grant # 0937060 to the Computing Research Association for the CIFellows Project, a National Science Foundation Graduate Research Fellowship Award Number DGE-0135733, ARL Number W911NF-06-2-0041, IEEE Robotics and Automation Society Graduate Fellowship, and a Microsoft HRI grant.


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Received: 2011-1-31
Accepted: 2011-3-19
Published Online: 2011-4-27
Published in Print: 2010-12-1

© Cindy L. Bethel et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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