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

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

3 Citations (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.

Original language	English
Title of host publication	Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers
Editors	Roberto Moreno-Díaz, Franz Pichler, Alexis Quesada-Arencibia
Publisher	Springer
Pages	619-625
Number of pages	7
ISBN (Print)	9783031253119
DOIs	https://doi.org/10.1007/978-3-031-25312-6_73
Publication status	Published - 2022
Event	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022 - Las Palmas de Gran Canaria, Spain Duration: 20 Feb 2022 → 25 Feb 2022

Publication series

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

Conference

Conference	18th International Conference on Computer Aided Systems Theory, EUROCAST 2022
Country/Territory	Spain
City	Las Palmas de Gran Canaria
Period	20.02.2022 → 25.02.2022

Keywords

Navigation
Odometry
Radar
Robotics

Access to Document

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

Cite this

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 (Eds.), Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers (pp. 619-625). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 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. editor / Roberto Moreno-Díaz ; Franz Pichler ; Alexis Quesada-Arencibia. Springer, 2022. pp. 619-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{c6c94aebb28340a2a63d810cbeab6fb4,

title = "Survey on Radar Odometry",

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",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022 ; Conference date: 20-02-2022 Through 25-02-2022",

year = "2022",

doi = "10.1007/978-3-031-25312-6_73",

language = "English",

isbn = "9783031253119",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "619--625",

editor = "Roberto Moreno-D{\'i}az and Franz Pichler and Alexis Quesada-Arencibia",

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

address = "Germany",

}

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 (eds), 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), vol. 13789 LNCS, Springer, pp. 619-625, 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022, Las Palmas de Gran Canaria, Spain, 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. ed. / Roberto Moreno-Díaz; Franz Pichler; Alexis Quesada-Arencibia. Springer, 2022. p. 619-625 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13789 LNCS).

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

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

UR - http://www.scopus.com/inward/record.url?scp=85151147038&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-25312-6_73

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

M3 - Conference contribution

AN - SCOPUS:85151147038

SN - 9783031253119

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

SP - 619

EP - 625

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

A2 - Moreno-Díaz, Roberto

A2 - Pichler, Franz

A2 - Quesada-Arencibia, Alexis

PB - Springer

T2 - 18th International Conference on Computer Aided Systems Theory, EUROCAST 2022

Y2 - 20 February 2022 through 25 February 2022

ER -

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, editors, Computer Aided Systems Theory – EUROCAST 2022 - 18th International Conference, Revised Selected Papers. Springer. 2022. p. 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