تقرير
Boreas: A Multi-Season Autonomous Driving Dataset
| العنوان: | Boreas: A Multi-Season Autonomous Driving Dataset |
|---|---|
| المؤلفون: | Burnett, Keenan, Yoon, David J., Wu, Yuchen, Li, Andrew Zou, Zhang, Haowei, Lu, Shichen, Qian, Jingxing, Tseng, Wei-Kang, Lambert, Andrew, Leung, Keith Y. K., Schoellig, Angela P., Barfoot, Timothy D. |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Robotics |
| الوصف: | 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 Comment: Accepted in IJRR as a data paper |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2203.10168 |
| رقم الأكسشن: | edsarx.2203.10168 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |