Boreas: Autonomous Driving Data with Lidar, Camera, and Radar in All-Weather Conditions
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Description
A multimodal autonomous driving dataset includes data from a 128-beam Velodyne Alpha-Prime lidar, a 5MP Blackfly camera, a 360-degree Navtech radar, and post-processed Applanix POS LV GNSS data. It was collected by ASRL over the course of a year in various weather conditions including sun, rain, and snow. The intended purpose is to enable benchmarking of long-term all-weather odometry and metric localization.
Use Cases
Benchmarking long-term odometry based on multi-sensor fusion of lidar, camera, and radar data.
Evaluating metric localization algorithms across different weather conditions.
Developing and testing sensor fusion models for autonomous driving.
Preparing for a future object detection benchmark using the described sensor suite.
Strengths
Includes data from a high-resolution 128-beam lidar and a 360-degree radar.
Captured over a year in diverse weather conditions (sun, rain, snow).
Multimodal sensor suite (lidar, camera, radar, GNSS) for cross-sensor benchmarking.
Limitations
Row count and dataset size are unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Last update date is unknown; freshness unverified.