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Assessing cooperation in human control of heterogeneous robots
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ACM/IEEE International Conference on Human-Robot Interaction archive
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction table of contents
Amsterdam, The Netherlands
SESSION: Technical papers table of contents
Pages 9-16  
Year of Publication: 2008
ISBN:978-1-60558-017-3
Authors
Jijun Wang  Quantum Leap Innovations, Newark, DE, USA
Michael Lewis  University of Pittsburgh, Pittsburgh, PA, USA
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

Human control of multiple robots has been characterized by the average demand of single robots on human attention. While this matches situations in which independent robots are controlled sequentially it does not capture aspects of demand associated with coordinating dependent actions among robots. This paper presents an extension of Crandall's neglect tolerance model intended to accommodate both coordination demands (CD) and heterogeneity among robots. The reported experiment attempts to manipulate coordination demand by varying the proximity needed to perform a joint task in two conditions and by automating coordination within subteams in a third. Team performance and the process measure CD were assessed for each condition. Automating cooperation reduced CD and improved performance. We discuss the utility of process measures such as CD to analyze and improve control performance.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Crandall, J., Goodrich, M., Olsen, D. and Nielsen, C. Validating human-robot interaction schemes in multitasking environments. IEEE Transactions on Systems, Man, and Cybernetics, Part A, 35(4):438--449, 2005.
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Gerkey, B. and Mataric, M. A formal framework for the study of task allocation in multi-robot systems. International Journal of Robotics Research, 23(9):939--954, 2004.
 
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Lewis, M., J. Wang, and S. Hughes, USARSim: Simulation for the Study of Human-Robot Interaction. Journal of Cognitive Engineering and Decision Making, 2007. 1(1): p. 98--120.
 
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Murphy, R.R. and J.L. Burke, Up from the Rubble: Lessons Learned about HRI from Search and Rescue, in Proceedings of the 49th Annual Meetings of the Human Factors and Ergonomics Society. 2005: Orlando.
 
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Nielsen, C., Goodrich, M., and Crandall, J. Experiments in human-robot teams. In Proceedings of the 2002 NRL Workshop on Multi-Robot Systems, October 2003
 
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Parasuraman, R., Galster, S., Squire, P., Furukawa, H. and Miller, C.. A flexible delegation-type interface enhances system performance in human supervision of multiple robots: Empirical studies with roboflag. IEEE Systems, Man and Cybernetics-Part A, 35(4):481--493, July 2005
 
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Scerri, P., et al., Coordinating large groups of wide area search munitions, in Recent Developments in Cooperative Control and Optimization, D. Grundel, R. Murphey, and P. Pandalos, Editors. 2004, Singapore: World Scientific. p. 451--480.
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Trouvain, B. and Wolf, H.. Evaluation of multi-robot control and monitoring performance. In Proceedings of the 2002 IEEE Int. Workshop on Robot and Human Interactive Communication, pages 111--116, September 2002.
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Wang, J. and Lewis, M. Assessing coordination overhead in control of robot teams, Proceedings of the 2007 International Conference on Systems, Man, and Cybernetics, 2007b, in press.


Collaborative Colleagues:
Jijun Wang: colleagues
Michael Lewis: colleagues