Journal
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
Volume 36, Issue 1, Pages 3-15Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0278364916679498
Keywords
Dataset; autonomous vehicles; long-term autonomy; mobile robotics; computer vision; cameras; LIDAR; GPS; stereo; localization; mapping; SLAM; RobotCar
Categories
Funding
- EPSRC [EP/M019918/1]
- EPSRC Leadership Fellowship [EP/I005021/1]
- Rhodes Scholarships
- Engineering and Physical Sciences Research Council [EP/K034472/1, GR/S62215/01, EP/M019918/1, EP/J012017/1, EP/I005021/1] Funding Source: researchfish
- EPSRC [EP/K034472/1, EP/J012017/1, EP/I005021/1] Funding Source: UKRI
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We present a challenging new dataset for autonomous driving: the Oxford RobotCar Dataset. Over the period of May 2014 to December 2015 we traversed a route through central Oxford twice a week on average using the Oxford RobotCar platform, an autonomous Nissan LEAF. This resulted in over 1000 km of recorded driving with almost 20 million images collected from 6 cameras mounted to the vehicle, along with LIDAR, GPS and INS ground truth. Data was collected in all weather conditions, including heavy rain, night, direct sunlight and snow. Road and building works over the period of a year significantly changed sections of the route from the beginning to the end of data collection. By frequently traversing the same route over the period of a year we enable research investigating long-term localization and mapping for autonomous vehicles in real-world, dynamic urban environments. The full dataset is available for download at: http://robotcar-dataset.robots.ox.ac.uk
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