Boreas: A Multi-Season Autonomous Driving Dataset

Keenan Burnett; David J. Yoon; Yuchen Wu; Andrew Zou Li; Haowei Zhang; Shichen Lu; Jingxing Qian; Wei-Kang Tseng; Andrew Lambert; Keith Y. K. Leung; Angela P. Schoellig; Timothy D. Barfoot

Boreas: A Multi-Season Autonomous Driving Dataset

Robotics 2023-01-27 v2

Authors: Keenan Burnett , David J. Yoon , Yuchen Wu , Andrew Zou Li , Haowei Zhang , Shichen Lu , Jingxing Qian , Wei-Kang Tseng , Andrew Lambert , Keith Y. K. Leung , Angela P. Schoellig , Timothy D. Barfoot

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Abstract

The Boreas dataset was collected by driving a repeated route over the course of one year, resulting in stark seasonal variations and adverse weather conditions such as rain and falling snow. In total, the Boreas dataset includes over 350km of driving data featuring a 128-channel Velodyne Alpha Prime lidar, a 360 $^\circ$ 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 https://www.boreas.utias.utoronto.ca

Keywords

autonomous driving

Cite

@article{arxiv.2203.10168,
  title  = {Boreas: A Multi-Season Autonomous Driving Dataset},
  author = {Keenan Burnett and David J. Yoon and Yuchen Wu and Andrew Zou Li and Haowei Zhang and Shichen Lu and Jingxing Qian and Wei-Kang Tseng and Andrew Lambert and Keith Y. K. Leung and Angela P. Schoellig and Timothy D. Barfoot},
  journal= {arXiv preprint arXiv:2203.10168},
  year   = {2023}
}

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Accepted in IJRR as a data paper

Boreas: A Multi-Season Autonomous Driving Dataset

Abstract

Keywords

Cite

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