On this page you will find project links and literature that have used the Oxford Radar RobotCar Dataset or related radar data.

If you have used this dataset and wish to be added to the list (or other radar papers / blogs / datasets you think helpful to a reader) please get in touch at radarrobotcardataset@robots.ox.ac.uk

Oxford Radar RobotCar Dataset Papers

Papers that use the dataset include:

Under the Radar: Learning to Predict Robust Keypoints for Odometry Estimation and Metric Localisation in Radar
Dan Barnes and Ingmar Posner
International Conference on Robotics and Automation (ICRA) 2020
[Paper] [Video] 

@inproceedings{UnderTheRadarICRA2020,
  address = {Paris},
  author = {Dan Barnes and Ingmar Posner},
  title = {Under the Radar: Learning to Predict Robust Keypoints for Odometry Estimation and Metric Localisation in Radar},
  booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},	
  url = {https://arxiv.org/abs/2001.10789},
  pdf = {https://arxiv.org/pdf/2001.10789.pdf},
  year = {2020}
}

RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar
Prannay Kaul, Daniele De Martini, Matthew Gadd, and Paul Newman
IEEE Intelligent Vehicles Symposium (IV) 2020
[Paper] 

@inproceedings{kaul2020rssnet,
  author = {Kaul, Prannay, and De Martini, Daniele, and Gadd, Matthew, and Newman, Paul},
  title = {{RSS-Net: Weakly-Supervised Multi-Class Semantic Segmentation with FMCW Radar}},
  booktitle={Proceedings of the IEEE Intelligent Vehicles Symposium (IV)},
  year = {2020}
}

Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance
Matthew Gadd, Daniele De Martini, and Paul Newman
IEEE/ION Position, Location and Navigation Symposium (PLANS) 2020
[Paper] 

@inproceedings{gadd2020lookaroundyou,
  author = {Gadd, Matthew, and De Martini, Daniele, and Newman, Paul},
  title = {{Look Around You: Sequence-based Radar Place Recognition with Learned Rotational Invariance}},
  booktitle={IEEE/ION Position, Location and Navigation Symposium (PLANS)},
  year = {2020}
}

Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning
Stefan Saftescu, Matthew Gadd, Daniele De Martini, Dan Barnes and Paul Newman
International Conference on Robotics and Automation (ICRA) 2020
[Paper] [Video] 

@inproceedings{KidnappedRadarICRA2020,
  address = {Paris},
  author = {S\u{a}ftescu, {\cb{S}}tefan and Gadd, Matthew, and De Martini, Daniele, and Barnes, Dan, and Newman, Paul},
  title = {{Kidnapped Radar: Topological Radar Localisation using Rotationally-Invariant Metric Learning}},
  booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},	
  url = {https://arxiv.org/abs/2001.09438},
  pdf = {https://arxiv.org/pdf/2001.09438.pdf},
  year = {2020}
}

Self-Supervised Localisation between Range Sensors and Overhead Imagery
Tim Y. Tang, Daniele De Martini, Shangzhe Wu and Paul Newman
Robotics: Science and Systems (RSS) 2020
[Paper] 

@inproceedings{Tang2020RSS,
  author = {Tim Y. Tang and Daniele De Martini and Shangzhe Wu and Paul Newman},
  title = {Self-Supervised Localisation between Range Sensors and Overhead Imagery},
  booktitle = {Robotics: Science and Systems (RSS)},	
  year = {2020}
}

RSL-Net: Localising in Satellite Images From a Radar on the Ground
Tim Y. Tang, Daniele De Martini, Dan Barnes and Paul Newman
International Conference on Robotics and Automation (ICRA) 2020
[Paper] 

@inproceedings{RSLNetICRA2020,
  address = {Paris},
  author = {Tim Y. Tang and Daniele De Martini and Dan Barnes and Paul Newman},
  title = {RSL-Net: Localising in Satellite Images From a Radar on the Ground},
  booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},	
  url = {https://arxiv.org/abs/2001.03233},
  pdf = {https://arxiv.org/pdf/2001.03233.pdf},
  year = {2020}
}

Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information
Dan Barnes, Rob Weston and Ingmar Posner
Conference on Robot Learning (CoRL) 2019
[Paper] [Video] 

@inproceedings{Barnes2019MaskingByMoving,
  author = {Dan Barnes and Rob Weston and Ingmar Posner},
  title = {Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information},
  booktitle = {{C}onference on {R}obot {L}earning ({CoRL})},
  url = {https://arxiv.org/pdf/1909.03752},
  pdf = {https://arxiv.org/pdf/1909.03752.pdf},
  year = {2019}
}

Some papers using similar, if not identical, Millimetre-Wave FMCW radar for mobile autonomy include:

Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision
David Williams, Daniele De Martini, Matthew Gadd, Letizia Marchegiani, and Paul Newman
Intelligent Transportation Systems (ITSC) Conference 2020
[Paper] 

@inproceedings{williams2020kotg,
  author = {Williams, David, and De Martini, Daniele, and Gadd, Matthew, and Marchegiani, Letizia, and Newman, Paul},
  title = {{Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision}},
  booktitle={IEEE Intelligent Transportation Systems Conference (ITSC)},
  year = {2020}
}

What Could Go Wrong? Introspective Radar Odometry in Challenging Environments
Roberto Aldera, Daniele De Martini, Matthew Gadd, and Paul Newman
Intelligent Transportation Systems (ITSC) Conference 2019
[Paper] 

@inproceedings{2019ITSC_aldera,
address = {Auckland, New Zealand},
author = {Aldera, Roberto and De Martini, Daniele and Gadd, Matthew and Newman, Paul},
booktitle = {{IEEE Intelligent Transportation Systems (ITSC) Conference}},
month = {October},
title = {{What Could Go Wrong? Introspective Radar Odometry in Challenging Environments}},
year = {2019},
Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2019ITSC_aldera.pdf}
}

Radar-only ego-motion estimation in difficult settings via graph matching
S. Cen and P. Newman
International Conference on Robotics and Automation (ICRA) 2019
[Paper] [Video] 

@inproceedings{2019ICRA_cen,
Title = {Radar-only ego-motion estimation in difficult settings via graph matching},
Author = {Cen,Sarah and Newman, Paul},
Booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada },
Year = {2019},
Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2019ICRA_cen.pdf}
}

Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision
Roberto Aldera, Daniele De Martini, Matthew Gadd, and Paul Newman
International Conference on Robotics and Automation (ICRA) 2019
[Paper] [Video] 

@inproceedings{2019ICRA_aldera,
Title = {Fast Radar Motion Estimation with a Learnt Focus of Attention using Weak Supervision},
Author = {Aldera, Roberto and De Martini, Daniele and Gadd, Matthew and Newman, Paul},
Booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada},
Year = {2019},
Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2019ICRA_aldera.pdf}
}

Probably Unknown: Deep Inverse Sensor Modelling Radar
R. Weston, S. Cen, P. Newman, and I. Poser
International Conference on Robotics and Automation (ICRA) 2019
[Paper] [Video] 

@inproceedings{ICRA19_weston,
Title = {Probably Unknown: Deep Inverse Sensor Modelling Radar},
Author = {Weston, Rob and Cen, Sarah and Newman, Paul and Posner, Ingmar},
Journal = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019},
Year = {2019},
Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/ICRA19_weston.pdf}
}

Precise Ego-Motion Estimation with Millimeter-Wave Radar under Diverse and Challenging Conditions
S. H. Cen and P. Newman
International Conference on Robotics and Automation (ICRA) 2018
[Paper] [Video] 

@article{2018ICRA_cen,
author = {Sarah H. Cen and Paul Newman},
title = {Precise Ego-Motion Estimation with Millimeter-Wave Radar under Diverse and Challenging Conditions},
journal = {Proceedings of the 2018 IEEE International Conference on Robotics and Automation},
address = {Oxford, UK},
year = {2018},
Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2018ICRA_cen.pdf}
}

Some additional blog posts that may be of interest include:

KAIST Radar-LIDAR Dataset

Concurrently to this release another Navtech Radar Dataset was submitted to the
ICRA 2019 Workshop on Dataset Generation and Benchmarking of SLAM Algorithms for Robotics and VR/AR.

Although significantly smaller in size than our release, the comparable setups should provide a great opportunity for cross validating approaches between datasets in different geographic locations.

If the reader was not aware of this data we would advise they have a look at their dataset which can be found at:
https://sites.google.com/view/dgbicra2019-radar-lidar

Radar Dataset for Robust Localization and Mapping in Urban Environment
Park, Yeong Sang and Jeong, Jinyong and Shin, Youngsik and Kim, Ayoung
ICRA 2019 Workshop on Dataset Generation and Benchmarking of SLAM Algorithms for Robotics and VR/AR
[Paper]