Metadata
Title
Oxford RobotCar Dataset
Category
undergraduate
UUID
f06d7cabf0784a5fb724cda8100f58aa
Source URL
https://robotcar-dataset.robots.ox.ac.uk/
Parent URL
https://ori.ox.ac.uk/robots/robotcar
Crawl Time
2026-03-09T02:56:57+00:00
Rendered Raw Markdown
# Oxford RobotCar Dataset

**Source**: https://robotcar-dataset.robots.ox.ac.uk/
**Parent**: https://ori.ox.ac.uk/robots/robotcar

Oxford Robotcar Dataset

## Datasets

View and download the available datasets

[More ›](https://robotcar-dataset.robots.ox.ac.uk/datasets/)

## Documentation

To help make use of the data

[More ›](https://robotcar-dataset.robots.ox.ac.uk/documentation/)

## Examples

Sample uses of the dataset

[More ›](https://robotcar-dataset.robots.ox.ac.uk/examples/)

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](https://robotcar-dataset.robots.ox.ac.uk/news)

#### [Real-time Kinematic Ground Truth](https://robotcar-dataset.robots.ox.ac.uk/news/rtk/)

 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](https://robotcar-dataset.robots.ox.ac.uk/news/long-term-autonomy-benchmark).

[Continue reading…](https://robotcar-dataset.robots.ox.ac.uk/news/rtk/)

[More news…](https://robotcar-dataset.robots.ox.ac.uk/news)

### 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]](javascript:void())[[PDF]](https://robotcar-dataset.robots.ox.ac.uk/images/robotcar_ijrr.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](https://robotcar-dataset.robots.ox.ac.uk/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]](javascript:void())[[PDF]](https://robotcar-dataset.robots.ox.ac.uk/images/RCD_RTK.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](http://creativecommons.org/licenses/by-nc-sa/4.0) and is intended for non-commercial academic use. If you are interested in using the dataset for commercial purposes please [contact us](https://robotcar-dataset.robots.ox.ac.uk/contact).

We take your privacy seriously: if you have any concerns about any of the content provided here, please [contact us](https://robotcar-dataset.robots.ox.ac.uk/contact).

### Register for downloads

Sign up to download files and receive updates about the dataset.

[Register](http://mrgdatashare.robots.ox.ac.uk/register/)

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