Conference item
Radar-only ego-motion estimation in difficult settings via graph matching
- Abstract:
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Radar detects stable, long-range objects under variable weather and lighting conditions, making it a reliable and versatile sensor well suited for ego-motion estimation. In this work, we propose a radar-only odometry pipeline that is highly robust to radar artifacts (e.g., speckle noise and false positives) and requires only one input parameter. We demonstrate its ability to adapt across diverse settings, from urban UK to off-road Iceland, achieving a scan matching accuracy of approximately 5.20 cm and 0.0929 deg when using GPS as ground truth (compared to visual odometry’s 5.77 cm and 0.1032 deg). We present algorithms for key point extraction and data association, framing the latter as a graph matching optimization problem, and provide an in-depth system analysis.
- Publication status:
- Published
- Peer review status:
- Reviewed (other)
Actions
Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 4.6MB, Terms of use)
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- Publisher copy:
- 10.1109/ICRA.2019.8793990
Authors
- Publisher:
- IEEE
- Host title:
- IEEE International Conference on Robotics and Automation, 2019.
- Journal:
- International Conference on Robotics and Automation More from this journal
- Publication date:
- 2019-08-12
- Acceptance date:
- 2019-01-31
- DOI:
- Keywords:
- Pubs id:
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pubs:1026217
- UUID:
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uuid:216cf226-3b70-486e-92b8-a1bb65e51299
- Local pid:
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pubs:1026217
- Source identifiers:
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1026217
- Deposit date:
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2019-07-03
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2019
- Notes:
- © IEEE 2019. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/ICRA.2019.8793990
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