Analysis of reactions towards failures and recovery strategies for autonomous robots

Human-robot interaction involving the failure of autonomous robots is not yet well understood. We conducted two online surveys with a total of 1200 participants in which people assessed situations where an autonomous robot experienced different kinds of failure. This information was used to construct a measurement scale of people's reaction to failure where positive values correspond with increasingly positive reactions and negative values with negative reactions. We then used this scale to compare different kinds of failure situations, including the severity of the failures, the context risk involved, and the effectiveness of different kinds of recovery strategies. We found evidence that the effectiveness of recovery strategies depends on the task, context, and severity of failure.

[1]  Pamela J. Hinds,et al.  Who Should I Blame? Effects of Autonomy and Transparency on Attributions in Human-Robot Interaction , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

[2]  R. Nisbett,et al.  Behavior as seen by the actor and as seen by the observer , 1973 .

[3]  David B. Kaber,et al.  Out‐of‐the‐loop performance problems and the use of intermediate levels of automation for improved control system functioning and safety , 1997 .

[4]  Ross A. Knepper,et al.  Recovering from failure by asking for help , 2015, Auton. Robots.

[5]  Harrison Si,et al.  Handbook of Research Methods in Social and Personality Psychology: Author Index , 2013 .

[6]  Robin R. Murphy,et al.  How UGVs physically fail in the field , 2005, IEEE Transactions on Robotics.

[7]  V. Folkes Consumer Reactions to Product Failure: An Attributional Approach , 1984 .

[8]  Aaron Steinfeld,et al.  Effects of blame on trust in human robot interaction , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

[9]  Holly A. Yanco,et al.  Classifying human-robot interaction: an updated taxonomy , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[10]  Raja Chatila,et al.  On Fault Tolerance and Robustness in Autonomous Systems , 2004 .

[11]  J. Krosnick,et al.  Survey research. , 1999, Annual review of psychology.

[12]  Adam J. Berinsky,et al.  Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk , 2012, Political Analysis.

[13]  Holly A. Yanco,et al.  Impact of robot failures and feedback on real-time trust , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[14]  Gerald Steinbauer,et al.  A Survey about Faults of Robots Used in RoboCup , 2012, RoboCup.

[15]  Siddhartha S. Srinivasa,et al.  Gracefully mitigating breakdowns in robotic services , 2010, 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[17]  Dan R. Olsen,et al.  Fan-out: measuring human control of multiple robots , 2004, CHI.

[18]  Clifford Nass,et al.  Critic, compatriot, or chump?: Responses to robot blame attribution , 2010, 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[19]  Tor W. Andreassen,et al.  Antecedents to satisfaction with service recovery , 2000 .

[20]  Stephanie Rosenthal,et al.  Is Someone in this Office Available to Help Me? , 2012, J. Intell. Robotic Syst..

[21]  Siddhartha S. Srinivasa,et al.  Perceived robot capability , 2015, 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).

[22]  David W. Payton,et al.  Do whatever works: A robust approach to fault-tolerant autonomous control , 2004, Applied Intelligence.