/CFEAR_Radarodometry

Implementation of CFEAR Radarodometry is described in

GNU General Public License v3.0GPL-3.0

Lidar-level localization with radar? The CFEAR approach to accurate, fast and robust large-scale radar odometry in diverse environments

News (January 2023) CFEAR is integrated in TBV Radar SLAM

News (April 2023): Article is now published in T-RO, code is released

Paper: T-RO or arXiv

  • A video demo of our latest results is shown here.

Watch the video

CFEAR-3 journal: "Lidar-level localization with radar? The CFEAR approach to accurate, fast and robust large-scale radar odometry in diverse environments"

citation
@ARTICLE{9969174,
  author={Adolfsson, Daniel and Magnusson, Martin and Alhashimi, Anas and Lilienthal, Achim J. and Andreasson, Henrik},
  journal={IEEE Transactions on Robotics}, 
  title={Lidar-Level Localization With Radar? The CFEAR Approach to Accurate, Fast, and Robust Large-Scale Radar Odometry in Diverse Environments}, 
  year={2023},
  volume={39},
  number={2},
  pages={1476-1495},
  doi={10.1109/TRO.2022.3221302}}

CFEAR-2 Conference article: CFEAR Radar odometry - Conservative Filtering for Efficient and Accurate Radar Odometry

Presented at IROS 2021

citation
@INPROCEEDINGS{9636253,  author={Adolfsson, Daniel and Magnusson, Martin and Alhashimi, Anas and Lilienthal, Achim J. and Andreasson, Henrik},
booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={CFEAR Radarodometry - Conservative Filtering for Efficient and Accurate Radar Odometry},
year={2021},  
volume={},  
number={},  
pages={5462-5469},
doi={10.1109/IROS51168.2021.9636253}}

CFEAR-1 workshop presentation: Oriented surface points for efficient and accurate radar odometry

  • The initial work on CFEAR was presented at Radar Perception for All-Weather Autonomy, a Half-Day Workshop at 2021 IEEE International Conference on Robotics and Automation (ICRA)
  • Workshop preprint
  • Workshop presentation
citation
@article{DBLP:journals/corr/abs-2109-09994,
  author    = {Daniel Adolfsson and Martin Magnusson and Anas W. Alhashimi and Achim J. Lilienthal and Henrik Andreasson},
  title     = {Oriented surface points for efficient and accurate radar odometry},
  journal   = {CoRR}, volume    = {abs/2109.09994}, year      = {2021}, url       = {https://arxiv.org/abs/2109.09994}, eprinttype = {arXiv}, eprint    = {2109.09994},
  timestamp = {Mon, 27 Sep 2021 15:21:05 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2109-09994.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
  

Relevant Publications

TBV Radar SLAM - trust but verify loop candidates

Large-scale introspective SLAM using Navtech radar.

Bibtex
@ARTICLE{10103570,
  author={Adolfsson, Daniel and Karlsson, Mattias and Kubelka, Vladimír and Magnusson, Martin and Andreasson, Henrik},
  journal={IEEE Robotics and Automation Letters}, 
  title={TBV Radar SLAM – Trust but Verify Loop Candidates}, 
  year={2023},
  volume={8},
  number={6},
  pages={3613-3620},
  doi={10.1109/LRA.2023.3268040}}
  

CorAl: Introspection for robust radar and lidar perception in diverse environments using differential entropy

Learns detection of small localization errors using Navtech radar.

Bibtex
@article{DBLP:journals/corr/abs-2109-09994,
  author    = {Daniel Adolfsson and Martin Magnusson and Anas W. Alhashimi and Achim J. Lilienthal and Henrik Andreasson},
  title     = {Oriented surface points for efficient and accurate radar odometry},
  journal   = {CoRR}, volume    = {abs/2109.09994}, year      = {2021}, url       = {https://arxiv.org/abs/2109.09994}, eprinttype = {arXiv}, eprint    = {2109.09994},
  timestamp = {Mon, 27 Sep 2021 15:21:05 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2109-09994.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
  

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