Towards Modeling Real-Time Trust in Asymmetric Human-Robot Collaborations

We are interested in enhancing the efficiency of human–robot collaborations, especially in “supervisor-worker” settings where autonomous robots work under the supervision of a human operator. We believe that trust serves a critical role in modeling the interactions within these teams, and also in streamlining their efficiency. We propose an operational formulation of human–robot trust on a short interaction time scale, which is tailored to a practical tele-robotics setting. We also report on a controlled user study that collected interaction data from participants collaborating with an autonomous robot to perform visual navigation tasks. Our analyses quantify key correlations between real-time human–robot trust assessments and diverse factors, including properties of failure events reflecting causal trust attribution, as well as strong influences from each user’s personality. We further construct and optimize a predictive model of users’ trust responses to discrete events, which provides both insights on this fundamental aspect of real-time human–machine interaction, and also has pragmatic significance for designing trust-aware robot agents.

[1]  Holly A. Yanco,et al.  Effects of changing reliability on trust of robot systems , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[2]  Gregory Dudek,et al.  A vision-based boundary following framework for aerial vehicles , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Ronald C. Arkin,et al.  Moral Decision Making in Autonomous Systems: Enforcement, Moral Emotions, Dignity, Trust, and Deception , 2012, Proceedings of the IEEE.

[4]  Terrence Fong,et al.  Collaboration, Dialogue, Human-Robot Interaction , 2001, ISRR.

[5]  Robert J. Hall.  Trusting your assistant , 1996, Proceedings of the 11th Knowledge-Based Software Engineering Conference.

[6]  Mark R. Lehto,et al.  Foundations for an Empirically Determined Scale of Trust in Automated Systems , 2000 .

[7]  Regina A. Pomranky,et al.  The role of trust in automation reliance , 2003, Int. J. Hum. Comput. Stud..

[8]  N Moray,et al.  Trust, control strategies and allocation of function in human-machine systems. , 1992, Ergonomics.

[9]  Ulf-Dietrich Reips,et al.  Interval-level measurement with visual analogue scales in Internet-based research: VAS Generator , 2008, Behavior research methods.

[10]  Cees J. H. Midden,et al.  The effects of errors on system trust, self-confidence, and the allocation of control in route planning , 2003, Int. J. Hum. Comput. Stud..

[11]  Sandra G. Hart,et al.  Nasa-Task Load Index (NASA-TLX); 20 Years Later , 2006 .

[12]  Bernard C. K. Choi,et al.  A Catalog of Biases in Questionnaires , 2004, Preventing chronic disease.

[13]  Jessie Y. C. Chen,et al.  A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction , 2011, Hum. Factors.

[14]  Terrence Fong,et al.  Collaboration, Dialogue, and Human-Robot Interaction , 2001 .

[15]  Gregory Dudek,et al.  Trust-driven interactive visual navigation for autonomous robots , 2012, 2012 IEEE International Conference on Robotics and Automation.

[16]  N. L. Chervany,et al.  THE MEANINGS OF TRUST , 2000 .

[17]  Andrew S. Clare,et al.  Modeling the Impact of Operator Trust on Performance in Multiple Robot Control , 2013, AAAI Spring Symposium: Trust and Autonomous Systems.

[18]  Ann M. Bisantz,et al.  Assessment of operator trust in and utilization of automated decision-aids under different framing conditions , 2001 .

[19]  Rosemarie E. Yagoda,et al.  You Want Me to Trust a ROBOT? The Development of a Human–Robot Interaction Trust Scale , 2012, International Journal of Social Robotics.

[20]  Ewart de Visser,et al.  Measurement of trust in human-robot collaboration , 2007, 2007 International Symposium on Collaborative Technologies and Systems.

[21]  Holly A. Yanco,et al.  Modeling trust to improve human-robot interaction , 2012 .