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Survey on Radar Odometry

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Computer Aided Systems Theory – EUROCAST 2022 (EUROCAST 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13789))

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Abstract

In this paper odometry approaches that use radar data are analyzed. First, the importance of odometry is discussed along with applications which usually require accurate odometry estimation. Moreover, sensors that are often used for odometry estimation are mentioned as well as the possible drawbacks that these sensors may have. Finally, the benefits of using radar as a source for odometry estimation are discussed. Furthermore, the approaches to perform radar odometry are categorized, and one categorization is evaluated as cardinal, namely the division between the direct method and the indirect method. Therefore, the direct method and the indirect method are investigated and their characteristics are juxtaposed.

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Acknowledgements

This work has been supported by the COMET-K2 Center of the Linz Center of Mechatronics (LCM) funded by the Austrian federal government and the federal state of Upper Austria.

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Authors and Affiliations

  1. Linz Center of Mechatronics GmbH, 4040, Linz, Austria

    Daniel Louback da Silva Lubanco, Markus Pichler-Scheder & Christian Kastl

  2. University of Applied Sciences Upper Austria, 4600, Wels, Austria

    Thomas Schlechter

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  1. Daniel Louback da Silva Lubanco
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  4. Christian Kastl
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Corresponding author

Correspondence to Daniel Louback da Silva Lubanco .

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Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University, Linz, Oberösterreich, Austria

    Franz Pichler

  3. Department of Computer Science and Institute of Cybernetics, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Louback da Silva Lubanco, D., Schlechter, T., Pichler-Scheder, M., Kastl, C. (2022). Survey on Radar Odometry. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2022. EUROCAST 2022. Lecture Notes in Computer Science, vol 13789. Springer, Cham. https://doi.org/10.1007/978-3-031-25312-6_73

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  • DOI: https://doi.org/10.1007/978-3-031-25312-6_73

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