Survey on Radar Odometry

Daniel Louback da Silva Lubanco; Thomas Schlechter; Markus Pichler-Scheder; Christian Kastl

doi:10.1007/978-3-031-25312-6_73

Survey on Radar Odometry

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

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

4 Zitate (Scopus)

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.

Originalsprache	Englisch
Titel	Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers
Redakteure/-innen	Roberto Moreno-Díaz, Franz Pichler, Alexis Quesada-Arencibia
Herausgeber (Verlag)	Springer
Seiten	619-625
Seitenumfang	7
ISBN (Print)	9783031253119
DOIs	https://doi.org/10.1007/978-3-031-25312-6_73
Publikationsstatus	Veröffentlicht - 2022
Veranstaltung	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022 - Las Palmas de Gran Canaria, Spanien Dauer: 20 Feb. 2022 → 25 Feb. 2022

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	13789 LNCS
ISSN (Print)	0302-9743
ISSN (elektronisch)	1611-3349

Konferenz

Konferenz	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022
Land/Gebiet	Spanien
Ort	Las Palmas de Gran Canaria
Zeitraum	20.02.2022 → 25.02.2022

Zugriff auf Dokument

10.1007/978-3-031-25312-6_73

Andere Dateien und Links

Link zur Publikation in Scopus

Zitieren

Louback da Silva Lubanco, D., Schlechter, T., Pichler-Scheder, M., & Kastl, C. (2022). Survey on Radar Odometry. in R. Moreno-Díaz, F. Pichler, & A. Quesada-Arencibia (Hrsg.), Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers (S. 619-625). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13789 LNCS). Springer. https://doi.org/10.1007/978-3-031-25312-6_73

Louback da Silva Lubanco, Daniel ; Schlechter, Thomas ; Pichler-Scheder, Markus et al. / Survey on Radar Odometry. Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz ; Franz Pichler ; Alexis Quesada-Arencibia. Springer, 2022. S. 619-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

keywords = "Navigation, Odometry, Radar, Robotics",

author = "{Louback da Silva Lubanco}, Daniel and Thomas Schlechter and Markus Pichler-Scheder and Christian Kastl",

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Louback da Silva Lubanco, D , Schlechter, T, Pichler-Scheder, M & Kastl, C 2022, Survey on Radar Odometry. in R Moreno-Díaz, F Pichler & A Quesada-Arencibia (Hrsg.), Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 13789 LNCS, Springer, S. 619-625, 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, Las Palmas de Gran Canaria, Spanien, 20.02.2022. https://doi.org/10.1007/978-3-031-25312-6_73

Survey on Radar Odometry. / Louback da Silva Lubanco, Daniel ; Schlechter, Thomas; Pichler-Scheder, Markus et al.
Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers. Hrsg. / Roberto Moreno-Díaz; Franz Pichler; Alexis Quesada-Arencibia. Springer, 2022. S. 619-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 13789 LNCS).

Publikation: Beitrag in Buch/Bericht/Tagungsband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Survey on Radar Odometry

AU - Louback da Silva Lubanco, Daniel

AU - Schlechter, Thomas

AU - Pichler-Scheder, Markus

AU - Kastl, Christian

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Navigation

KW - Odometry

KW - Radar

KW - Robotics

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers

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Louback da Silva Lubanco D , Schlechter T, Pichler-Scheder M, Kastl C. Survey on Radar Odometry. in Moreno-Díaz R, Pichler F, Quesada-Arencibia A, Hrsg., Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers. Springer. 2022. S. 619-625. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-25312-6_73