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Intelligent Autonomous Systems 13 pp 307–319Cite as

Layered Mission and Path Planning for MAV Navigation with Partial Environment Knowledge

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

Abstract

Successful operation of micro aerial vehicles in partially known environments requires globally consistent plans based on incomplete environment models and quick reactions to unknown obstacles by means of real-time planning of collision-free trajectories. In this paper, we propose a complete layered mission and navigation planning system based on coarse prior knowledge and local maps from omnidirectional onboard obstacle perception. We generate trajectories in a multilayered approach: from mission planning to global and local trajectory planning to motion control.

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Acknowledgments

This work has been supported by grant BE 2556/8 of German Research Foundation (DFG).

Author information

Authors and Affiliations

  1. Autonomous Intelligent Systems Group, Computer Science Institute VI, University of Bonn, 53113, Bonn, Germany

    Matthias Nieuwenhuisen & Sven Behnke

Authors
  1. Matthias Nieuwenhuisen
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  2. Sven Behnke
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Corresponding author

Correspondence to Matthias Nieuwenhuisen .

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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© 2016 Springer International Publishing Switzerland

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Nieuwenhuisen, M., Behnke, S. (2016). Layered Mission and Path Planning for MAV Navigation with Partial Environment Knowledge. 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_23

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  • DOI: https://doi.org/10.1007/978-3-319-08338-4_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08337-7

  • Online ISBN: 978-3-319-08338-4

  • eBook Packages: EngineeringEngineering (R0)

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