English

OORD: The Oxford Offroad Radar Dataset

Robotics 2024-05-28 v2

Abstract

There is a growing academic interest as well as commercial exploitation of millimetre-wave scanning radar for autonomous vehicle localisation and scene understanding. Although several datasets to support this research area have been released, they are primarily focused on urban or semi-urban environments. Nevertheless, rugged offroad deployments are important application areas which also present unique challenges and opportunities for this sensor technology. Therefore, the Oxford Offroad Radar Dataset (OORD) presents data collected in the rugged Scottish highlands in extreme weather. The radar data we offer to the community are accompanied by GPS/INS reference - to further stimulate research in radar place recognition. In total we release over 90GiB of radar scans as well as GPS and IMU readings by driving a diverse set of four routes over 11 forays, totalling approximately 154km of rugged driving. This is an area increasingly explored in literature, and we therefore present and release examples of recent open-sourced radar place recognition systems and their performance on our dataset. This includes a learned neural network, the weights of which we also release. The data and tools are made freely available to the community at https://oxford-robotics-institute.github.io/oord-dataset.

Keywords

Cite

@article{arxiv.2403.02845,
  title  = {OORD: The Oxford Offroad Radar Dataset},
  author = {Matthew Gadd and Daniele De Martini and Oliver Bartlett and Paul Murcutt and Matt Towlson and Matthew Widojo and Valentina Muşat and Luke Robinson and Efimia Panagiotaki and Georgi Pramatarov and Marc Alexander Kühn and Letizia Marchegiani and Paul Newman and Lars Kunze},
  journal= {arXiv preprint arXiv:2403.02845},
  year   = {2024}
}