List of Datasets

UAV

VIODE

Visual-Inertial Odometry

Simulated stereo-inertial quadrotor benchmark with three environments, four controlled dynamic levels per environment, instance masks and simulator pose ground truth.

Metadata: Complete Metadata needs review Released 2021

Primary places to inspect, download, read about, or reproduce the dataset.

Download

Not reported

Code

Not reported

Supplementary

Not reported

Quick facts

Vehicle type
UAV
Environment
Indoor, Outdoor
Data origin
Simulation
Sensor count
3
Ground truth
Available
Calibration
Parameters Only
Annotations
Available

Sensor overview

High-level sensor availability before the detailed sensor records below.

Cameras

2 reported

IMUs

1 reported

GNSS

Not reported

LiDAR

Not reported

Radar

Not reported

Pitot tube

Not reported

Magnetometers

Not reported

Barometers

Not reported

UWB

Not reported

Ground truth

Reference scope, method, rate, coverage, and provenance.

Scope Method Reference system Count Rate Coverage Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
6DoF Other Not reported Not reported 200 Hz Full Reference provenance
External
Measured using equipment independent of the platform’s normal onboard sensor pipeline.
Derived
Computed primarily from the dataset’s own recorded sensors.
Hybrid
Combines independent reference equipment with onboard measurements.
Unknown
Reference notes
Simulator-provided AirSim ground-truth 6-DoF trajectory for every sequence; the 20 Hz rendering poses are a subsampling of this reference, not a separate reference system.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Parameters Only
Processed parameters
Available
Raw calibration data
Not reported
Calibration targets
Not reported

Parameters only

Processed calibration parameters are reported, but raw calibration data is not reported.

Notes

Ground-truth stereo intrinsics and extrinsics and camera-IMU extrinsics are supplied.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Simulated IMU omits rotor vibration and has lower noise than real UAV data.

Dynamic objects are cars moving at constant speeds along designated paths.

VINS-Mask evaluation uses ground-truth masks rather than predicted segmentation.

Cameras

simulated_stereo

Model
Not reported
Setup
Stereo
Count
1
Effective cameras
2
Modality
Rgb
Resolution
752 x 480
Rate
20 Hz
Shutter
Global
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Simulated stereo pair; 5 cm baseline. Reported FOV is 90 degrees without an axis, so horizontal and vertical values remain unknown. Instance masks accompany both cameras at 20 Hz.

IMUs

AirSim simulated IMU

Model
Not reported
Count
1
Accel / gyro
Not reported

GNSS

Not reported

LiDAR

Not reported

Radar

Not reported

Pitot tube

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Available
Format
Not reported
Class count
Not reported
Semantic segmentation Not reported
Instance segmentation Available
Object detection Not reported
Optical flow Not reported
Depth ground truth Not reported

Citation

Citation key and BibTeX kept at the end of the page for reference.

Citation key
minoda2021viode

BibTeX

@misc{minoda2021viode,
  title={VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments},
  author={Minoda, Koji and Schilling, Fabian and W{\"u}est, Valentin and Floreano, Dario and Yairi, Takehisa},
  year={2021},
  eprint={2102.05965},
  archivePrefix={arXiv},
  primaryClass={cs.RO}
}

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