Mobile Robot Yielding Cues for Human-Robot Spatial Interaction*

Mobile robots are increasingly being deployed in public spaces such as shopping malls, airports, and urban sidewalks. Most of these robots are designed with human-aware motion planning capabilities but are not designed to communicate with pedestrians. Pedestrians encounter these robots without prior understanding of the robots’ behaviour, which can cause discomfort, confusion, and delayed social acceptance. In this research, we explore the common human-robot interaction at a doorway or bottleneck in a structured environment. We designed and evaluated communication cues used by a robot when yielding to a pedestrian in this scenario. We conducted an online user study with 102 participants using videos of a set of robot-to-human yielding cues. Results show that a Robot Retreating cue was the most socially acceptable cue. Repeated measures and Friedman’s ANOVAs on components of social acceptability were statistically significant (p = .01) and had small and medium effect sizes (ηp2 = .04, ηp2 = .08). The results of this work help guide the development of mobile robots for public spaces.

[1]  Moritz Körber,et al.  Theoretical Considerations and Development of a Questionnaire to Measure Trust in Automation , 2018, Advances in Intelligent Systems and Computing.

[2]  S. Kauppinen,et al.  European medium-term conflict detection field trials [ATC] , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[3]  Atsushi Watanabe,et al.  Communicating robotic navigational intentions , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[4]  Florian G. Kaiser,et al.  How to make nonhumanoid mobile robots more likable: Employing kinesic courtesy cues to promote appreciation. , 2019, Applied ergonomics.

[5]  Dirk Helbing,et al.  Self-Organizing Pedestrian Movement , 2001 .

[6]  Marc Hanheide,et al.  Hesitation Signals in Human-Robot Head-on Encounters : A Pilot Study , 2014, 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[7]  Kerstin Dautenhahn,et al.  Methodological Issues in HRI: A Comparison of Live and Video-Based Methods in Robot to Human Approach Direction Trials , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

[8]  Elizabeth A. Croft,et al.  Design and impact of hesitation gestures during human-robot resource conflicts , 2013, HRI 2013.

[9]  Rachid Alami,et al.  Human-aware robot navigation: A survey , 2013, Robotics Auton. Syst..

[10]  Klaus Bengler,et al.  Dominance and movement cues of robot motion: A user study on trust and predictability , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

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

[12]  Rachid Alami,et al.  Synthesizing Robot Motions Adapted to Human Presence - A Planning and Control Framework for Safe and Socially Acceptable Robot Motions , 2010, Int. J. Soc. Robotics.

[13]  Jack Thomas,et al.  Right of Way, Assertiveness and Social Recognition in Human-Robot Doorway Interaction , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[14]  Josef F. Krems,et al.  Deceleration parameters and their applicability as informal communication signal between pedestrians and automated vehicles , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[15]  Peter Collett,et al.  Patterns of Public Behaviour: Collision Avoidance on a Pedestrian Crossing , 1974 .

[16]  Andreas Krause,et al.  Robot navigation in dense human crowds: Statistical models and experimental studies of human–robot cooperation , 2015, Int. J. Robotics Res..

[17]  A. Joshi,et al.  Likert Scale: Explored and Explained , 2015 .

[18]  William D. Smart,et al.  Towards more efficient navigation for robots and humans , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[19]  Jonathan P. How,et al.  Socially aware motion planning with deep reinforcement learning , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[20]  M. Lauckner,et al.  ‘Hey robot, please step back!’ - exploration of a spatial threshold of comfort for human-mechanoid spatial interaction in a hallway scenario , 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

[21]  That assumption of normality , 2020 .

[22]  Terrence Fong,et al.  A Survey of Methods for Safe Human-Robot Interaction , 2017, Found. Trends Robotics.

[23]  Alexandra Kirsch,et al.  Influence of legibility on perceived safety in a virtual human-robot path crossing task , 2012, 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication.

[24]  Stephan Winter,et al.  Negotiation Between Vehicles and Pedestrians for the Right of Way at Intersections , 2019, IEEE Transactions on Intelligent Transportation Systems.

[25]  Takayuki Kanda,et al.  Social Coordination for Looking-Together Situations , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).