ABSTRACT
People are increasingly working with robots in teams and recent research has focused on how human-robot teams function, but little attention has yet been paid to the role of social signaling behavior in human-robot teams. In a controlled experiment, we examined the role of backchanneling and task complexity on team functioning and perceptions of the robots' engagement and competence. Based on results from 73 participants interacting with autonomous humanoid robots as part of a human-robot team (one participant, one confederate, and three robots), we found that when robots used backchanneling team functioning improved and the robots were seen as more engaged. Ironically, the robots using backchanneling were perceived as less competent than those that did not. Our results suggest that backchanneling plays an important role in human-robot teams and that the design and implementation of robots for human-robot teams may be more effective if backchanneling capability is provided.
Supplemental Material
- ARToolKit. {Software}. Available from: http://www.hitl.washington.edu/artoolkit/.Google Scholar
- Aviezer, H., et al., Angry, Disgusted, or Afraid? Psychological Science, 2008. 19(7): p. 724--732.Google Scholar
- Barsade, S. G., The Ripple Effect: Emotional Contagion and its Influence on Group Behavior. Administrative Science Quarterly, 2002. 47(4): p. 644--675.Google Scholar
- Barsade, S. G. and D. E. Gibson, Why does affect matter in organizations? The Academy of Management Perspectives, 2007. 21(1): p. 36--59.Google Scholar
- Bethel, C. L. and R. R. Murphy, Affective expression in appearance constrained robots, in Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction. 2006, ACM: Salt Lake City, Utah, USA. p. 327--328. Google ScholarDigital Library
- Bethel, C. L. and R. R. Murphy, Non-facial/non-verbal methods of affective expression as applied to robot-assisted victim assessment, in Proceedings of the ACM/IEEE international conference on Human-robot interaction. 2007, ACM: Arlington, Virginia, USA. p. 287--294. Google ScholarDigital Library
- Bickmore, T. W. and R. W. Picard, Towards caring machines, in CHI '04 extended abstracts on Human factors in computing systems. 2004, ACM: Vienna, Austria. p. 1489--1492. Google ScholarDigital Library
- Breazeal, C., et al. 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.Google ScholarCross Ref
- Breazeal, C. and B. Scassellati. How to build robots that make friends and influence people. in Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on. 1999.Google ScholarCross Ref
- Breazeal, C. L., Designing sociable robots. 2004: The MIT Press. Google ScholarDigital Library
- Bruce, A., I. Nourbakhsh, and R. Simmons. The role of expressiveness and attention in human-robot interaction. in Robotics and Automation, 2002. Proceedings. ICRA '02. IEEE International Conference on. 2002.Google ScholarCross Ref
- Brunken, R., J. L. Plass, and D. Leutner, Direct Measurement of Cognitive Load in Multimedia Learning. Educational Psychologist, 2003. 38(1): p. 53--61.Google Scholar
- Campbell, D. J., Task complexity: A review and analysis. The Academy of Management Review, 1988. 13(1): p. 40--52.Google Scholar
- CARMEN. Robot Navigation Toolkit. Available from: http://carmen.sourceforge.net/.Google Scholar
- Casper, J. and R. R. Murphy, Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 2003. 33(3): p. 367--385. Google ScholarDigital Library
- Cereproc. {Software}. Available from http://www.cereproc.com/.Google Scholar
- Clark, H. H. and S. A. Brennan, Grounding in Communication, in Perspectives on socially shared cognition, L. B. Resnick, J. M. Levine, and S. D. Teasley, Editors. 1991, APA Book.: Washington.Google Scholar
- Coan, J. A. and J. M. Gottman, The Specific Affect Coding System (SPAFF), in Handbook of emotion elicitation and assessment., J. A. Coan and J. J. B. Allen, Editors. 2007, New York, NY, US: Oxford University Press. p. 267--285.Google Scholar
- Dennis, A. R. and S. T. Kinney, Testing Media Richness Theory in the New Media: The Effects of Cues, Feedback, and Task Equivocality. Information Systems Research, 1998. 9(3): p. 256--274. Google ScholarDigital Library
- Earley, P. C., Influence of information, choice and task complexity upon goal acceptance, performance, and personal goals. Journal of Applied Psychology, 1985. 70(3): p. 481--491.Google Scholar
- Felps, W., T. R. Mitchell, and E. Byington, How, when, and why bad apples spoil the barrel: Negative group members and dysfunctional groups. Research in organizational behavior, 2006. 27: p. 175--222.Google Scholar
- Fincannon, T., et al. Evidence of the need for social intelligence in rescue robots. in 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2004. Sendai, Japan: IEEE.Google ScholarCross Ref
- Fong, T., I. Nourbakhsh, and K. Dautenhahn, A survey of socially interactive robots. Robotics and Autonomous Systems, 2003. 42(3): p. 143--166.Google Scholar
- Gockley, R., R. Simmons, and J. Forlizzi. Modeling Affect in Socially Interactive Robots. in Robot and Human Interactive Communication, 2006. ROMAN 2006. The 15th IEEE International Symposium on. 2006.Google ScholarCross Ref
- Jacob, M., et al., Gestonurse: a robotic surgical nurse for handling surgical instruments in the operating room. Journal of Robotic Surgery, 2012. 6(1): p. 53--63.Google Scholar
- Johnson, C., Gender, Legitimate Authority, and Leader-Subordinate Conversations. American Sociological Review, 1994. 59(1): p. 122--135.Google Scholar
- Jones, H. and P. Hinds. Extreme work teams: using swat teams as a model for coordinating distributed robots. in ACM conference on Computer supported cooperative work, CSCW'02. 2002. New Orleans, Louisiana, USA.: ACM. Google ScholarDigital Library
- Jung, M. F., J. Chong, and L. J. Leifer. Group Hedonic Balance and Pair Programming Performance: Affective Interaction Dynamics as indicators of Performance. in ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'12). 2012. Austin, Texas, USA. Google ScholarDigital Library
- Kahn, W. A., Psychological Conditions of Personal Engagement and Disengagement at Work. Academy of Management Journal, 1990. 33(4): p. 692--724.Google Scholar
- Keltner, D. and J. Haidt, Social functions of emotions, in Emotions: Currrent issues and future directions, T. J. M. G. A. Bonanno, Editor. 2001, Guilford Press: New York, NY, US. p. 192--213.Google Scholar
- Knutson, B., Facial expressions of emotion influence interpersonal trait inferences. Journal of Nonverbal Behavior, 1996. 20(3): p. 165--182.Google Scholar
- Lee, K. M., et al., Can Robots Manifest Personality?: An Empirical Test of Personality Recognition, Social Responses, and Social Presence in Human-Robot Interaction. Journal of Communication, 2006. 56(4): p. 754--772.Google Scholar
- Lewis, K., Measuring transactive memory systems in the field: Scale development and validation. Journal of Applied Psychology, 2003. 88(4): p. 587--604.Google Scholar
- Liu, C., et al. Generation of nodding, head tilting and eye gazing for human-robot dialogue interaction. in 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 2012. Kyoto, Japan: IEEE. Google ScholarDigital Library
- Maynard, D. C. and M. D. Hakel, Effects of objective and subjective task complexity on performance. Human Performance; Human Performance, 1997. 10(4): p. 303--330.Google Scholar
- Murphy, R. R., Human-robot interaction in rescue robotics. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 2004. 34(2): p. 138--153. Google ScholarDigital Library
- Murphy, R. R. and J. L. Burke, Up from the Rubble: Lessons Learned about HRI from Search and Rescue. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2005. 49(3): p. 437--441.Google ScholarCross Ref
- Murphy, R. R., et al., Emotion-based control of cooperating heterogeneous mobile robots. Robotics and Automation, IEEE Transactions on, 2002. 18(5): p. 744--757.Google Scholar
- Nass, C. and B. Reeves, The media equation: How people treat computers, televisions, and new media as real people and places. 1996, Cambridge University Press. Google ScholarDigital Library
- Parasuraman, R. and C. A. Miller, Trust and etiquette in high-criticality automated systems. Commun. ACM, 2004. 47(4): p. 51--55. Google ScholarDigital Library
- Pasupathi, M., et al., Responsive Listening in Long- Married Couples: A Psycholinguistic Perspective. Journal of Nonverbal Behavior, 1999. 23(2): p. 173--193.Google Scholar
- Rose, R., M. Scheutz, and P. Schermerhorn. Empirical investigations into the believability of robot affect. in Proceedings of the AAAI Spring Symposium. 2008.Google Scholar
- Schegloff, E. A., Sequence organization in interaction: A primer in conversation analysis I. Vol. 1. 2007: Cambridge Univ Pr.Google Scholar
- Shah, J., et al., Improved human-robot team performance using chaski, a human-inspired plan execution system, in Proceedings of the 6th international conference on Human-robot interaction. 2011, ACM: Lausanne, Switzerland. p. 29--36. Google ScholarDigital Library
- Sidner, C. L., et al., Explorations in engagement for humans and robots. Artificial Intelligence, 2005. 166(1): p. 140--164. Google ScholarDigital Library
- Sidner, C. L., et al., The effect of head-nod recognition in human-robot conversation, in Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction. 2006, ACM: Salt Lake City, Utah, USA. p. 290--296. Google ScholarDigital Library
- Sphinx, C. {Software}. Available from: http://cmusphinx.sourceforge.net/.Google Scholar
- Stubbs, K., P. J. Hinds, and D. Wettergreen, Autonomy and Common Ground in Human-Robot Interaction: A Field Study. Intelligent Systems, IEEE, 2007. 22(2): p. 42--50. Google ScholarDigital Library
- Takayama, L., V. Groom, and C. Nass, I'm sorry, Dave: i'm afraid i won't do that: social aspects of human-agent conflict, in Proceedings of the 27th international conference on Human factors in computing systems. 2009, ACM: Boston, MA, USA. p. 2099--2108. Google ScholarDigital Library
- van Gerven, P. W. M., et al., Modality and variability as factors in training the elderly. Applied Cognitive Psychology, 2006. 20(3): p. 311--320.Google Scholar
- Vicon. {Software}. Available from: http://www.vicon.com/.Google Scholar
- Wang, E., et al., Effects of head movement on perceptions of humanoid robot behavior, in Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction. 2006, ACM: Salt Lake City, Utah, USA. p. 180--185. Google ScholarDigital Library
- Wang, L. and C. Chen, A Combined Optimization Method for Solving the Inverse Kinematics Problem of Mechanical Manipulators. IEEE Trans. On Robotics and Applications, 1991. 7(4): p. 489--499.Google Scholar
- Watson, D., L. A. Clark, and A. Tellegen, Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 1988. 54(6): p. 1063--1070.Google Scholar
- Weick, K. E., The Vulnerable System: An Analysis of the Tenerife Air Disaster. Journal of Management, 1990. 16(3): p. 571--593.Google Scholar
- Yamazaki, A., et al., Precision timing in human-robot interaction: coordination of head movement and utterance, in Proceedings of the twenty-sixth annual SIGCHI conference on Human factors in computing systems CHI'08. 2008, ACM: Florence, Italy. p. 131--140. Google ScholarDigital Library
Index Terms
- Engaging robots: easing complex human-robot teamwork using backchanneling
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