Towards Dynamic Team Formation for Robot Ensembles

We present an investigation of dynamic team formation strategies for robot ensembles performing a collection of single and two-robot tasks. Specifically, we consider the abstract "stick and pebble" problem, as a variation of the "stick pulling" problem discussed in the literature...

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Bibliographic Details
Main Authors: Mather, T. William (Author), Hsieh, M. Ani (Author), Frazzoli, Emilio (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2011-08-30T19:02:47Z.
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Online Access:Get fulltext
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100 1 0 |a Mather, T. William  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Laboratory for Information and Decision Systems  |e contributor 
100 1 0 |a Frazzoli, Emilio  |e contributor 
100 1 0 |a Frazzoli, Emilio  |e contributor 
700 1 0 |a Hsieh, M. Ani  |e author 
700 1 0 |a Frazzoli, Emilio  |e author 
245 0 0 |a Towards Dynamic Team Formation for Robot Ensembles 
260 |b Institute of Electrical and Electronics Engineers,   |c 2011-08-30T19:02:47Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/65554 
520 |a We present an investigation of dynamic team formation strategies for robot ensembles performing a collection of single and two-robot tasks. Specifically, we consider the abstract "stick and pebble" problem, as a variation of the "stick pulling" problem discussed in the literature. We present a formulation of the dynamic team formation problem that is independent of ensemble size and develop a macroscopic analytical description of the ensemble dynamics. The macroscopic model is then used to determine the optimal teaming strategy for two different performance metrics. We present agent-based simulation results to support the validity of our macroscopic analysis. 
546 |a en_US 
655 7 |a Article 
773 |t 2010 IEEE International Conference on Robotics and Automation (ICRA)