Human-Robot Teaming in Urban Search and Rescue

Although current urban search and rescue (USAR) robots are little more than remotely controlled cameras, the end goal is for them to work alongside humans as trusted teammates. Natural language communications and performance data are collected as a team of humans works to carry out a simulated search and rescue task in an uncertain virtual environment. Conditions are tested emulating a remotely controlled robot versus an intelligent one. Differences in performance, situation awareness (SA), trust, and workload are measured. The Intelligent robot condition resulted in higher levels of performance and operator SA.

[1]  Robin R. Murphy,et al.  Human-robot interaction in rescue robotics , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[2]  Robin R. Murphy,et al.  Moonlight in Miami : A Field Study of Human-Robot Interaction in the Context of an Urban Search and Rescue Disaster Response Training Exercise , 2003 .

[3]  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).

[4]  Stephen M. Fiore,et al.  Towards Modeling Social-Cognitive Mechanisms in Robots to Facilitate Human-Robot Teaming , 2013, Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

[5]  Bernhard Nebel,et al.  Coming up With Good Excuses: What to do When no Plan Can be Found , 2010, Cognitive Robotics.

[6]  Holly A. Yanco,et al.  Potential measures for detecting trust changes , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[7]  R. Murphy,et al.  Up from the Rubble: Lessons Learned about HRI from Search and Rescue , 2005 .

[8]  Robin R. Murphy,et al.  Moonlight in Miami: a field study of human-robot interaction in the context of an urban search and rescue disaster response training exercise , 2004 .

[9]  Cynthia Breazeal,et al.  An Empirical Analysis of Team Coordination Behaviors and Action Planning With Application to Human–Robot Teaming , 2010, Hum. Factors.

[10]  Florian Jentsch,et al.  Human-animal teams as an analog for future human-robot teams , 2012 .

[11]  Matthias Scheutz,et al.  Towards a Framework for Integrated Natural Language Processing Architectures for Social Robots , 2008, NLPCS.

[12]  Robin R. Murphy,et al.  Human-robot interactions during the robot-assisted urban search and rescue response at the World Trade Center , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[13]  Thomas Fincannon,et al.  The Effects of Autonomy and Cognitive Abilities on Workload and Supervisory Control of Unmanned Systems , 2012 .

[14]  Holly A. Yanco,et al.  Robot confidence and trust alignment , 2013, 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[15]  Mary L. Cummings,et al.  Teamwork in controlling multiple robots , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[16]  Robin R. Murphy Marsupial and Shape-Shifting Robots for Urban Search and Rescue , 2000, IEEE Intell. Syst..

[17]  Michele Galvano,et al.  [Where am I?]. , 2014, Giornale italiano di nefrologia : organo ufficiale della Societa italiana di nefrologia.

[18]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[19]  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).

[20]  Hadas Kress-Gazit,et al.  Sorry Dave, I'm Afraid I Can't Do That: Explaining Unachievable Robot Tasks Using Natural Language , 2013, Robotics: Science and Systems.

[21]  Florian Jentsch,et al.  The importance of shared mental models and shared situation awareness for transforming robots from tools to teammates , 2012, Defense, Security, and Sensing.

[22]  Julie A. Adams,et al.  Human-Robot Interaction Design: Understanding User Needs and Requirements , 2005 .

[23]  E. Salas,et al.  Theories of Team Cognition: Cross-Disciplinary Perspectives , 2013 .

[24]  Matthias Scheutz,et al.  Tell me when and why to do it! Run-time planner model updates via natural language instruction , 2012, 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI).