Decentralized Planning for Complex Missions with Dynamic Communication Constraints

This paper extends the consensus-based bundle algorithm (CBBA), a distributed task allocation framework previously developed by the authors, to address complex missions for a team of heterogeneous agents in a dynamic environment. The extended algorithm proposes appropriate handling of time windows o...

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Bibliographic Details
Main Authors: Ponda, Sameera S. (Contributor), Redding, Josh (Contributor), Choi, Han-Lim (Contributor), How, Jonathan P. (Contributor), Vavrina, Matt (Author), Vian, John (Author)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2010-10-06T14:20:21Z.
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Online Access:Get fulltext
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042 |a dc 
100 1 0 |a Ponda, Sameera S.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a How, Jonathan P.  |e contributor 
100 1 0 |a Ponda, Sameera S.  |e contributor 
100 1 0 |a Redding, Josh  |e contributor 
100 1 0 |a Choi, Han-Lim  |e contributor 
100 1 0 |a How, Jonathan P.  |e contributor 
700 1 0 |a Redding, Josh  |e author 
700 1 0 |a Choi, Han-Lim  |e author 
700 1 0 |a How, Jonathan P.  |e author 
700 1 0 |a Vavrina, Matt  |e author 
700 1 0 |a Vian, John  |e author 
245 0 0 |a Decentralized Planning for Complex Missions with Dynamic Communication Constraints 
260 |b Institute of Electrical and Electronics Engineers,   |c 2010-10-06T14:20:21Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/58889 
520 |a This paper extends the consensus-based bundle algorithm (CBBA), a distributed task allocation framework previously developed by the authors, to address complex missions for a team of heterogeneous agents in a dynamic environment. The extended algorithm proposes appropriate handling of time windows of validity for tasks, fuel costs of the vehicles, and heterogeneity in the agent capabilities, while preserving the robust convergence properties of the original algorithm. An architecture to facilitate real-time task replanning in a dynamic environment is also presented, along with methods to handle varying communication constraints and dynamic network topologies. Simulation results and experimental flight tests in an indoor test environment verify the proposed task planning methodology for complex missions. 
520 |a United States. Air Force Office of Scientific Research (grant FA9550-08-1-0086) 
520 |a Multidisciplinary University Research Initiative (MURI) (FA9550-08-1-0356) 
520 |a Boeing Scientific Research Laboratories 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the American Control Conference, 2010