  In this paper we present The Oxford Radar RobotCar Dataset, a new dataset for
researching scene understanding using Millimetre-Wave FMCW scanning radar data.
The target application is autonomous vehicles where this modality is robust to
environmental conditions such as fog, rain, snow, or lens flare, which
typically challenge other sensor modalities such as vision and LIDAR.
  The data were gathered in January 2019 over thirty-two traversals of a
central Oxford route spanning a total of 280km of urban driving. It encompasses
a variety of weather, traffic, and lighting conditions. This 4.7TB dataset
consists of over 240,000 scans from a Navtech CTS350-X radar and 2.4 million
scans from two Velodyne HDL-32E 3D LIDARs; along with six cameras, two 2D
LIDARs, and a GPS/INS receiver. In addition we release ground truth optimised
radar odometry to provide an additional impetus to research in this domain. The
full dataset is available for download at:
ori.ox.ac.uk/datasets/radar-robotcar-dataset
