Abstract
The Boreas dataset was collected by driving a repeated route over the course of 1 year, resulting in stark seasonal variations and adverse weather conditions such as rain and falling snow. In total, the Boreas dataset includes over 350 km of driving data featuring a 128-channel Velodyne Alpha-Prime lidar, a 360° Navtech CIR304-H scanning radar, a 5MP FLIR Blackfly S camera, and centimetre-accurate post-processed ground truth poses. Our dataset will support live leaderboards for odometry, metric localization, and 3D object detection. The dataset and development kit are available at boreas.utias.utoronto.ca.
Cite
CITATION STYLE
Burnett, K., Yoon, D. J., Wu, Y., Li, A. Z., Zhang, H., Lu, S., … Barfoot, T. D. (2023). Boreas: A multi-season autonomous driving dataset. International Journal of Robotics Research, 42(1–2), 33–42. https://doi.org/10.1177/02783649231160195
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