CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry Article Swipe
Daniel Adolfsson
,
Martin Magnusson
,
Anas Alhashimi
,
Achim J. Lilienthal
,
Henrik Andreasson
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/iros51168.2021.9636253
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/iros51168.2021.9636253
This paper presents the accurate, highly efficient, and learning-free method CFEAR Radarodometry for large-scale radar odometry estimation. By using a filtering technique that keeps the k strongest returns per azimuth and by additionally filtering the radar data in Cartesian space, we are able to compute a sparse set of oriented surface points for efficient and accurate scan matching. Registration is carried out by minimizing a point-to-line metric and robustness to outliers is achieved using a Huber loss. We were able to additionally reduce drift by jointly registering the latest scan to a history of keyframes and found that our odometry method generalizes to different sensor models and datasets without changing a single parameter. We evaluate our method in three widely different environments and demonstrate an improvement over spatially cross-validated state-of-the-art with an overall translation error of 1.76% in a public urban radar odometry benchmark, running at 55Hz merely on a single laptop CPU thread.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/iros51168.2021.9636253
- OA Status
- green
- Cited By
- 43
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3157400318
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3157400318Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/iros51168.2021.9636253Digital Object Identifier
- Title
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CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar OdometryWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-09-27Full publication date if available
- Authors
-
Daniel Adolfsson, Martin Magnusson, Anas Alhashimi, Achim J. Lilienthal, Henrik AndreassonList of authors in order
- Landing page
-
https://doi.org/10.1109/iros51168.2021.9636253Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-94463Direct OA link when available
- Concepts
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Odometry, Computer science, Robustness (evolution), Artificial intelligence, Visual odometry, Computer vision, Radar, Outlier, Laptop, Mobile robot, Robot, Biochemistry, Telecommunications, Gene, Chemistry, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
43Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 10, 2023: 16, 2022: 8, 2021: 3Per-year citation counts (last 5 years)
- References (count)
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48Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.landing_page_url | https://doi.org/10.1109/iros51168.2021.9636253 |
| publication_date | 2021-09-27 |
| publication_year | 2021 |
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