Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset

Abstract – We describe the release of reference data towards a challenging long-term localisation and mapping benchmark based on the large-scale Oxford RobotCar Dataset. The release includes 72 traversals of a route through Oxford, UK, gathered in all illumination, weather and traffic conditions, and is representative of the conditions an autonomous vehicle would be expected to operate reliably in. Using post-processed raw GPS, IMU, and static GNSS base station recordings, we have produced a globally-consistent centimetre-accurate ground truth for the entire year-long duration of the dataset. Coupled with a planned online benchmarking service, we hope to enable quantitative evaluation and comparison of different localisation and mapping approaches focusing on long-term autonomy for road vehicles in urban environments challenged by changing weather.

Dataset – The RTK files are downloadable from this page:

Further Info – For more information please read our paper:

  • [PDF] W. Maddern, G. Pascoe, M. Gadd, D. Barnes, B. Yeomans, and P. Newman, “Real-time Kinematic Ground Truth for the Oxford RobotCar Dataset,” arXiv preprint arXiv: 2002.10152, 2020.
    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 = {},
    pdf = {},
    year = {2020}