DurLAR is a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery for multi-modal autonomous driving applications. Compared to existing autonomous driving task datasets, DurLAR has the following novel features:

• High vertical resolution LiDAR with 128 channels, which is twice that of any existing datasets, full 360 degree depth, range accuracy to ±2 cm at 20-50m.
• Ambient illumination (near infrared) and reflectivity panoramic imagery are made available in the Mono16 format (2048 × 128 resolution), with this being only dataset to make this provision.
• No rolling shutter effect, as our flash LiDAR captures all 128 channels simultaneously.
• Ambient illumination data is recorded via an on-board lux meter, which is again not available in previous datasets.
• High-fidelity GNSS/INS available via an onboard OxTS navigation unit operating at 100 Hz and receiving position and timing data from multiple GNSS con-stellations in addition to GPS.
• KITTI data format adopted as the de facto dataset format such that it can be parsed using both the DurLAR development kit and existing KITTI-compatible tools.
• Diversity over repeated locations such that the dataset has been collected under diverse environmental and weather conditions over the same driving route with additional variations in the time of day relative to environmental conditions.

Sensor placement

• LiDAR: Ouster OS1-128 LiDAR sensor with 128 channels vertical resolution

• Stereo Camera: Carnegie Robotics MultiSense S21 stereo camera with grayscale, colour, and IR enhanced imagers, 2048x1088 @ 2MP resolution

• GNSS/INS: OxTS RT3000v3 global navigation satellite and inertial navigation system, supporting localization from GPS, GLONASS, BeiDou, Galileo, PPP and SBAS constellations

• Lux Meter: Yocto Light V3, a USB ambient light sensor (lux meter), measuring ambient light up to 100,000 lux