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World Modeling

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Springer Handbook of Robotics

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Abstract

In this chapter we describe popular ways to represent the environment of a mobile robot. For indoor environments, which are often stored using two-dimensional representations, we discuss occupancy grids, line maps, topological maps, and landmark-based representations. Each of these techniques has its own advantages and disadvantages. Whilst occupancy grid maps allow for quick access and can efficiently be updated, line maps are more compact. Also landmark-based maps can efficiently be updated and maintained, however, they do not readily support navigation tasks such as path planning like topological representations do.

Additionally, we discuss approaches suited for outdoor terrain modeling. In outdoor environments, the flat-surface assumption underling many mapping techniques for indoor environments is no longer valid. A very popular approach in this context are elevation and variants maps, which store the surface of the terrain over a regularly spaced grid. Alternatives to such maps are point clouds, meshes, or three-dimensional grids, which provide a greater flexibility but have higher storage demands.

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Abbreviations

2-D:

two-dimensional

2.5-D:

two-and-a-half-dimensional

3-D:

three-dimensional

EKF:

extended Kalman filter

EM:

expectation maximization

SLAM:

simultaneous localization and mapping

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Freiburg, Georges-Koehler-Allee 79, 79110, Freiburg, Germany

    Wolfram Burgard

  2. The Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, PA 15213, Pittsburgh, USA

    Martial Hebert

  3. Institute for Computer Science VI, University of Bonn, Friedrich-Ebert-Allee 144, 53113, Bonn, Germany

    Maren Bennewitz

Authors
  1. Wolfram Burgard
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  2. Martial Hebert
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  3. Maren Bennewitz
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Corresponding author

Correspondence to Wolfram Burgard .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Naples Federico II, Via Claudio 21, 80125, Naples, Italy

    Bruno Siciliano

  2. Department of Computer Sciences, Artificial Intelligence Laboratory, Stanford University, 450 Serra Mall, CA 94305, Stanford, USA

    Oussama Khatib

Video-References

Video-References

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OctoMap visualization available from http://handbookofrobotics.org/view-chapter/45/videodetails/79

:

3-D textured model of urban environments available from http://handbookofrobotics.org/view-chapter/45/videodetails/269

:

Service robot navigation in urban environments available from http://handbookofrobotics.org/view-chapter/45/videodetails/270

:

Learning navigation cost grids available from http://handbookofrobotics.org/view-chapter/45/videodetails/271

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Burgard, W., Hebert, M., Bennewitz, M. (2016). World Modeling. In: Siciliano, B., Khatib, O. (eds) Springer Handbook of Robotics. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-32552-1_45

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  • DOI: https://doi.org/10.1007/978-3-319-32552-1_45

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