UAV
NTU VIRAL
Aerial visual-inertial, UWB ranging and LiDAR localization
Eighteen aerial recordings with stereo grayscale cameras, dual lidar, inertial/magnetic streams, UWB ranging and partial laser-tracked prism positions.
Access links
Primary places to inspect, download, read about, or reproduce the dataset.
Quick facts
- Vehicle type
- UAV
- Environment
- Indoor, Outdoor
- Data origin
- Real-world
- Sensor count
- 11
- Ground truth
- Available
- Calibration
- Partial Raw Data
- Annotations
- Not reported
Sensor overview
High-level sensor availability before the detailed sensor records below.
Ground truth
Reference scope, method, rate, coverage, and provenance.
| Scope | Method | Reference system | Count | Rate | Coverage |
Reference provenance
|
|---|---|---|---|---|---|---|
| 3D position | Total station | Leica Nova MultiStation · MS60 | Not reported | 20 Hz | Partial · Flight Prism Tracking Where Supplied; Intermittent Tracking Gaps, Especially in Original SBS Recordings. |
Reference provenance
External
Accuracy and notes
|
Calibration and synchronization
Reported calibration level, reproducibility signals, and supporting notes.
- Level
- Partial Raw Data
- Processed parameters
- Available
- Raw calibration data
- Available
- Calibration targets
- chessboard
Reproducible calibration data
Raw calibration data is reported, so users can reproduce or inspect the calibration process.
Notes
Stereo calibration image pairs and a stereo/IMU Kalibr bag are listed publicly. Complete raw support for lidar, UWB and flexible extrinsics is not established; body-to-prism correction is required.
Known or intentional limitations
Reported constraints and characteristics to check before using the dataset.
Prism is nearly 0.4 m from body origin and flexible mount introduces relative motion.
Reference gaps occur during SBS tracking loss.
UWB multipath, orientation and low signal strength cause missing/unreliable ranges.
Dark appearance from exposure settings challenges direct vision methods.
Timestamps include documented offsets; stereo hardware trigger does not synchronize every stream.
Official release notes identify Ouster point-cloud/IMU timing jitter and provide a regularization script.
Data are licensed CC BY-NC-SA 4.0 for noncommercial use.
Cameras
Camera 1
- Model
- uEye 1221 LE
- Setup
- Stereo
- Count
- 1
- Effective cameras
- 2
- Modality
- Grayscale
- Resolution
- 752 x 480
- Rate
- 10 Hz
- Shutter
- Global
- Lens type
- Not Reported
- HFOV
- Not reported
- VFOV
- Not reported
- Notes
- One forward stereo pair of two physical monochrome cameras. External trigger synchronizes exposures; ROS image publish timestamps typically differ below 3 ms.
IMUs
Main body-frame IMU
- Model
- VectorNav VN100
- Count
- 1
- Accel / gyro
- 385 / 385 Hz
Ouster integrated IMUs
- Model
- Not reported
- Count
- 2
- Accel / gyro
- 100 / 100 Hz
GNSS
LiDAR
Ouster OS1-16 Gen1
- Model or name
- Ouster OS1-16 Gen1
- Count
- 2
- Dimensions
- 3
- Rate
- 10 Hz
- Channels
- 16
- Range
- Not reported
Additional sensors
Magnetometer
- Model
- VectorNav VN100
- Count
- 1
- Rate
- 385 Hz
- Notes
- Magnetic-field output from the same main VN100 unit, not an additional physical sensor package.
UWB
- Model
- Humatics P440
- Name
- Onboard ranging radios
- Count
- 2
- Placement
- platform
- Rate
- 68.571 Hz
- Role
- tag
- Notes
- Two mobile radios with four antennas/nodes and three fixed anchors. Rate is aggregate mobile-to-anchor messages, not per-radio/per-pair cadence. Inter-anchor measurements and anchor coordinates are 5.714 Hz.
UWB
- Name
- Environmental ranging anchors
- Count
- 1
- Placement
- environment
- Rate
- 5.714 Hz
- Role
- anchor
- Notes
- Three fixed anchor nodes participate in released inter-anchor/mobile ranging. Physical radio count/model not explicitly established; rate is aggregate inter-anchor topic, not per-node.
Annotations
Reported annotation availability and task support.
- Availability
- Not reported
- Format
- Not reported
- Class count
- Not reported
Citation
Citation key and BibTeX kept at the end of the page for reference.
@article{nguyen2022ntu,
title={NTU VIRAL: A Visual-Inertial-Ranging-Lidar Dataset, From an Aerial Vehicle Viewpoint},
author={Nguyen, Thien-Minh and Yuan, Shenghai and Cao, Muqing and Lyu, Yang and Nguyen, Thien Hoang and Xie, Lihua},
journal={The International Journal of Robotics Research},
volume={41}, number={3}, pages={270--280}, year={2022}
}
Dataset corrections
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