Radar-only ego-motion estimation in difficult settings via graph matching
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 po...
Published in: | 2019 International Conference on Robotics and Automation (ICRA) |
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Online Access: | https://doi.org/10.1109/ICRA.2019.8793990 https://ora.ox.ac.uk/objects/uuid:216cf226-3b70-486e-92b8-a1bb65e51299 |
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ftuloxford:oai:ora.ox.ac.uk:uuid:216cf226-3b70-486e-92b8-a1bb65e51299 2023-05-15T16:48:51+02:00 Radar-only ego-motion estimation in difficult settings via graph matching Cen, S Newman, P 2019-07-03 https://doi.org/10.1109/ICRA.2019.8793990 https://ora.ox.ac.uk/objects/uuid:216cf226-3b70-486e-92b8-a1bb65e51299 unknown IEEE doi:10.1109/ICRA.2019.8793990 https://ora.ox.ac.uk/objects/uuid:216cf226-3b70-486e-92b8-a1bb65e51299 https://doi.org/10.1109/ICRA.2019.8793990 info:eu-repo/semantics/openAccess Conference item 2019 ftuloxford https://doi.org/10.1109/ICRA.2019.8793990 2022-06-28T20:07:42Z 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. Conference Object Iceland ORA - Oxford University Research Archive 2019 International Conference on Robotics and Automation (ICRA) 298 304 |
institution |
Open Polar |
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ORA - Oxford University Research Archive |
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ftuloxford |
language |
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description |
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. |
format |
Conference Object |
author |
Cen, S Newman, P |
spellingShingle |
Cen, S Newman, P Radar-only ego-motion estimation in difficult settings via graph matching |
author_facet |
Cen, S Newman, P |
author_sort |
Cen, S |
title |
Radar-only ego-motion estimation in difficult settings via graph matching |
title_short |
Radar-only ego-motion estimation in difficult settings via graph matching |
title_full |
Radar-only ego-motion estimation in difficult settings via graph matching |
title_fullStr |
Radar-only ego-motion estimation in difficult settings via graph matching |
title_full_unstemmed |
Radar-only ego-motion estimation in difficult settings via graph matching |
title_sort |
radar-only ego-motion estimation in difficult settings via graph matching |
publisher |
IEEE |
publishDate |
2019 |
url |
https://doi.org/10.1109/ICRA.2019.8793990 https://ora.ox.ac.uk/objects/uuid:216cf226-3b70-486e-92b8-a1bb65e51299 |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
doi:10.1109/ICRA.2019.8793990 https://ora.ox.ac.uk/objects/uuid:216cf226-3b70-486e-92b8-a1bb65e51299 https://doi.org/10.1109/ICRA.2019.8793990 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1109/ICRA.2019.8793990 |
container_title |
2019 International Conference on Robotics and Automation (ICRA) |
container_start_page |
298 |
op_container_end_page |
304 |
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1766038945723842560 |