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Doppler-aware odometry from FMCW scanning radar

Abstract:
This work explores Doppler information from a millimetre-Wave (mm-W) Frequency-Modulated Continuous-Wave (FMCW) scanning radar to make odometry estimation more robust and accurate. Firstly, doppler information is added to the scan masking process to enhance correlative scan matching. Secondly, we train a Neural Network (NN) for regressing forward velocity directly from a single radar scan; we fuse this estimate with the correlative scan matching estimate and show improved robustness to bad estimates caused by challenging environment geometries, e.g. narrow tunnels. We test our method with a novel custom dataset which is released with this work at https://ori.ox.ac.uk/publications/datasets.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ITSC57777.2023.10422412

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0001-6121-5839


More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/W011344/1
Programme:
RAILS
More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/V000748/1
Programme:
From Sensing to Collaboration


Publisher:
IEEE
Host title:
2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)
Pages:
5126-5132
Publication date:
2024-02-13
Acceptance date:
2023-07-10
Event title:
26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023)
Event location:
Bilbao, Bizkaia, Spain
Event website:
https://2023.ieee-itsc.org/
Event start date:
2023-09-24
Event end date:
2023-09-28
DOI:
EISSN:
2153-0017
ISSN:
2153-0009


Language:
English
Keywords:
Pubs id:
1582337
Local pid:
pubs:1582337
Deposit date:
2023-12-14
ARK identifier:

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