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Intelligent Autonomous Systems 13 pp 445–458Cite as

Voronoi-Based Heuristic for Nonholonomic Search-Based Path Planning

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 302)

Abstract

This paper proposes the use of a Voronoi-based heuristic to significantly speed up search-based nonholonomic path planning. Using generalized Voronoi diagrams (GVD) and in this manner exploiting geometric information about the obstacles, the presented approach is able to considerably reduce computation time while satisfying differential constraints using motion primitives for exploration. A key advantage compared to the common use of Euclidean heuristics is the inherent ability to avoid local minima of the cost function, which can be caused by, e.g., concave obstacles. Therefore, the application of the Voronoi-based heuristic is particularly beneficial in densely cluttered environments.

Keywords

  • Search-based planning
  • Nonholonomic planning
  • Voronoi
  • GVD
  • Heuristic
  • Primitive motion A*

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Author information

Authors and Affiliations

  1. Leibniz University of Hannover, 30167, Hannover, Germany

    Qi Wang, Markus Wulfmeier & Bernardo Wagner

Authors
  1. Qi Wang
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  2. Markus Wulfmeier
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  3. Bernardo Wagner
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Corresponding author

Correspondence to Qi Wang .

Editor information

Editors and Affiliations

  1. Information Engineering, University of Padua, Padua, Italy

    Emanuele Menegatti

  2. Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

    Nathan Michael

  3. Fachbereich Informatik, Technische Universität Kaiserslautern Arbeitsgruppe Robotersysteme, Kaiserslautern, Germany

    Karsten Berns

  4. Integrated Information Technology, Aoyama Gakuin University, Tokyo, Japan

    Hiroaki Yamaguchi

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Wang, Q., Wulfmeier, M., Wagner, B. (2016). Voronoi-Based Heuristic for Nonholonomic Search-Based Path Planning. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_33

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  • DOI: https://doi.org/10.1007/978-3-319-08338-4_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08337-7

  • Online ISBN: 978-3-319-08338-4

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