Oxford RobotCar Dataset
Source: https://robotcar-dataset.robots.ox.ac.uk/ Parent: https://ori.ox.ac.uk/robots/robotcar
Oxford Robotcar Dataset
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The Oxford RobotCar Dataset contains over 100 repetitions of a consistent route through Oxford, UK, captured over a period of over a year. The dataset captures many different combinations of weather, traffic and pedestrians, along with longer term changes such as construction and roadworks.
News
Real-time Kinematic Ground Truth
2020-02-20
We are pleased to release the ground truth reference data towards a planned challenging long-term localisation and mapping Oxford RobotCar Long-Term Autonomy Benchmark.
Citation
To use this dataset in your publications please cite the following paper:
| W. Maddern, G. Pascoe, C. Linegar and P. Newman, "1 Year, 1000km: The Oxford RobotCar Dataset", The International Journal of Robotics Research (IJRR), 2016. [Bibtex][PDF] |
@article{RobotCarDatasetIJRR, \
Author = {Will Maddern and Geoff Pascoe and Chris Linegar and Paul Newman}, \
Title = {{1 Year, 1000km: The Oxford RobotCar Dataset}}, \
Journal = {The International Journal of Robotics Research (IJRR)}, \
Volume = {36}, \
Number = {1}, \
Pages = {3-15}, \
Year = {2017}, \
doi = {10.1177/0278364916679498}, \
URL = \
{http://dx.doi.org/10.1177/0278364916679498}, \
eprint = \
{http://ijr.sagepub.com/content/early/2016/11/28/0278364916679498.full.pdf+html}, \
Pdf = {http://robotcar-dataset.robots.ox.ac.uk/images/robotcar_ijrr.pdf}}
If you use the released ground truth, please also cite the following paper:
| W. Maddern, G. Pascoe, M. Gadd, D. Barnes, B. Yeomans, and P. Newman, "Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset", in arXiv preprint arXiv: 2002.10152, 2020. [Bibtex][PDF] |
@article{RCDRTKArXiv, \
author = {Will Maddern and Geoffrey Pascoe and Matthew Gadd and Dan Barnes and Brian Yeomans and Paul Newman}, \
title = {Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset}, \
journal = {arXiv preprint arXiv: 2002.10152}, \
url = {https://arxiv.org/pdf/2002.10152}, \
pdf = {https://arxiv.org/pdf/2002.10152.pdf}, \
year = {2020} \
}
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License and is intended for non-commercial academic use. If you are interested in using the dataset for commercial purposes please contact us.
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