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Pareto Optimal Coordination on Roadmaps

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Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 17))

Abstract

Given a collection of robots sharing a common environment, assume that each possesses an individual roadmap for its C-space and a cost function for attaining a goal. Vector-valued (or Pareto) optima for collision-free coordination are by no means unique: in fact, continua of optimal coordinations are possible. However, for cylindrical obstacles (those defined by pairwise interactions), we prove a finite bound on the number of optimal coordinations. For such systems, we present an exact algorithm for reducing a coordination scheme to its Pareto optimal representative.

Supported by NSF PECASE DMS-0337713 [RG] and NSF IIS-0296126 [JO,SL].

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Michael Erdmann Mark Overmars David Hsu Frank van der Stappen

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Ghrist, R., O’Kane, J.M., LaValle, S.M. Pareto Optimal Coordination on Roadmaps. In: Erdmann, M., Overmars, M., Hsu, D., van der Stappen, F. (eds) Algorithmic Foundations of Robotics VI. Springer Tracts in Advanced Robotics, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10991541_13

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  • DOI: https://doi.org/10.1007/10991541_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25728-8

  • Online ISBN: 978-3-540-31506-3

  • eBook Packages: EngineeringEngineering (R0)

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