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Model-Based Path Planning

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Sensing and Control for Autonomous Vehicles

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 474))

Abstract

Model-based path planning for autonomous vehicles may incorporate knowledge of the dynamics, the environment, the planning objective, and available resources. In this chapter, we first review the most commonly used dynamic models for autonomous ground , surface, underwater, and air vehicles. We then discuss five common approaches to path planning—optimal control , level set methods, coarse planning with path smoothing , motion primitives, and random sampling—along with a qualitative comparison. The chapter includes a brief interlude on optimal path planning for kinematic car models. The aim of this chapter is to provide a high-level introduction to the field and to suggest relevant topics for further reading.

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Acknowledgements

We thank Thomas Battista, Mazen Farhood, David Grymin, James McMahon, and Michael Otte for reviewing a draft of this chapter and providing helpful comments. The first author would also like to acknowledge support from the American Society for Engineering Education’s NRL Postdoctoral Fellowship program. The second author gratefully acknowledges the support of the ONR under Grant Nos. N00014-14-1-0651 and N00014-16-1-2749.

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Authors and Affiliations

  1. American Society for Engineering Education, Washington D.C., USA

    Artur Wolek

  2. Virginia Tech, Blacksburg, VA, USA

    Craig A. Woolsey

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  1. Artur Wolek
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  2. Craig A. Woolsey
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Correspondence to Artur Wolek .

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Editors and Affiliations

  1. Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Thor I. Fossen

  2. Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Kristin Y. Pettersen

  3. Eindhoven University of Technology (TuE), Eindhoven, The Netherlands

    Henk Nijmeijer

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Wolek, A., Woolsey, C.A. (2017). Model-Based Path Planning. In: Fossen, T., Pettersen, K., Nijmeijer, H. (eds) Sensing and Control for Autonomous Vehicles. Lecture Notes in Control and Information Sciences, vol 474. Springer, Cham. https://doi.org/10.1007/978-3-319-55372-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-55372-6_9

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  • Online ISBN: 978-3-319-55372-6

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