Supporting multiple robot systems
Event Date: 2006-07-15 04:00
| Author: Julie A. Adams
Affiliation: Vanderbilt University
Title: Supporting multiple robot systems
Keywords: Robotics, Coalition Formation, and Human-Robot Interaction.
Issue Date: July 15, 2006
Bibliography: Julie A. Adams, "Supporting multiple robot systems", Journal of the Robotics Society of Japan, Vol. 24, No. 5, pp.579-581, 2006.
Abstract:
As the desire to remove humans from dangerous situations, such as exposure to harmful chemicals, increases, so does the need to develop UMV systems. There is also a desire to increase the number of deployed UMVs while limiting the number of humans supervising the system. Ideally, UMV systems would be autonomous, however such technology is not yet available. Therefore, human interaction capabilities that permit a single human to supervise a number of semi-autonomous UMVs is required. One of our research focuses has been the development of autonomous coalition formation for the multiple robot-multiple task problem. Our algorithm determines coalitions based upon the UMV’s capabilities (i.e. sensors and actuators) while considering the balance and fault tolerance of the resulting coalition. The coalition formation algorithm has been evaluated with up to forty simulated UMVs and with up to fourteen actual UMVs that are allocated to multiple simultaneous tasks. The assignment of UMVs to multiple coalitions from a large set of possible UMVs is a very involved task in the best of circumstances when the human is not taxed with other demanding tasks. A next step for this research is to incorporate the coalition formation algorithm with our HRI research.
References:
[1] J.A. Adams, “Human Management of a Hierarchical System for the Control of Multiple Mobile Robots. Ph.D. Dissertation, University of Pennsylvania, 1995.
[2] E. Balas and M. Padberg, “Set partitioning: a survey”, SIAM Review 18, pp.710--760, 1976.
[3] J. J. Burke, R. R. Murphy, M. Coovert and D. Riddle, “Moonlight in Miami: A field study of human-robot interaction in the context of an urban search and rescue disaster response training exercise”, Journal of Human-Computer Interaction 19(1-2) pp.85--116, 2004.
[4] B. P. Gerkey and M. J. Matarić, “A formal analysis and taxonomy of task allocation in multi-robot systems,” International Journal of Robotics Research, vol. 23, no. 9, pp. 939--954, 2004.
[5] K. Hoffman and M. Padberg, “Solving airline crew-scheduling problems by branch-and-cut”, Management Science 39(6), pp.667--682, 1993.
[6] T. W. Sandholm, K. Larson, M. Andersson, O. Shehory, and F. Tomhe, “Coalition structure generation with worst case guarantees”, Artificial Intelligence 111(1-2), pp.209--238, 1999.
[7] L. Vig and J. A. Adams, “Multi-Robot Coalition Formation”, IEEE Transactions on Robotics, under review, 2006.
[8] L. Vig and J. A. Adams, “Balancing in Multi-Robot Teams”, under review, 2006. |
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