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The Minimum Constraint Removal Problem with Three Robotics Applications

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Book cover Algorithmic Foundations of Robotics X

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 86))

Abstract

This paper formulates a new Minimum Constraint Removal (MCR) motion planning problem in which the objective is to remove the fewest geometric constraints necessary to connect a start and goal state with a free path. I present a probabilistic roadmap motion planner for MCR in continuous configuration spaces. The planner operates by constructing increasingly refined roadmaps, and efficiently solves discrete MCR problems on these networks. A number of new theoretical results are given for discrete MCR, including a proof that it is NP-hard by reduction from SET-COVER, and I describe two search algorithms that perform well in practice. The motion planner is proven to produce the optimal MCR with probability approaching 1 as more time is spent, and its convergence rate is improved with various efficient sampling strategies. The planner is demonstrated on three example applications: generating human-interpretable excuses for failure, motion planning under uncertainty, and rearranging movable obstacles.

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Author information

Authors and Affiliations

  1. School of Informatics and Computing, Indiana University, Bloomington, IN, USA

    Kris Hauser

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  1. Kris Hauser
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Correspondence to Kris Hauser .

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Editors and Affiliations

  1. Associate Professor of Aeronautics and, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Emilio Frazzoli

  2. MIT Comp. Sci. & Artificial Intel. Lab., Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Tomas Lozano-Perez

  3. Robust Robotics Group, Massachusetts Institute of Technology CSAIL, Cambridge, Massachusetts, USA

    Nicholas Roy

  4. Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Daniela Rus

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Hauser, K. (2013). The Minimum Constraint Removal Problem with Three Robotics Applications. In: Frazzoli, E., Lozano-Perez, T., Roy, N., Rus, D. (eds) Algorithmic Foundations of Robotics X. Springer Tracts in Advanced Robotics, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36279-8_1

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  • DOI: https://doi.org/10.1007/978-3-642-36279-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36278-1

  • Online ISBN: 978-3-642-36279-8

  • eBook Packages: EngineeringEngineering (R0)

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