List of Datasets

Automotive

UTBM Robocar / EU Long-term

Long-term vehicle mapping and roundabout perception

Repeated urban/suburban multimodal car recordings include four LiDAR devices, surround vision, radar and RTK trajectories.

Metadata: Complete Metadata source documented Released 2018

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

Supplementary

Not reported

Quick facts

Vehicle type
Automotive
Environment
Outdoor
Data origin
Real-world
Sensor count
13
Ground truth
Available
Calibration
Parameters Only
Annotations
Not reported

Sensor overview

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

Cameras

6 reported

IMUs

1 reported

GNSS

1 reported

LiDAR

4 reported

Radar

1 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.
3D position RTK GNSS Magellan ProFlex 500 Not reported 15 Hz Partial · Rtk Valid Intervals 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.
Hybrid
Reference notes
External-base RTK corrections with an onboard receiver. January 10 has no GNSS listed, January 31 lists ordinary GPS, and July 18 has partial RTK data. Valid-fix intervals and independent error remain unquantified.

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

Official camera-info YAML provides intrinsics/distortion and stereo rectification; playback supplies the platform transform tree. Complete raw calibration-session inventory and achieved extrinsic accuracy remain unknown.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

The maintained table lists eleven long-term recording groups and two roundabout groups. The ten roundabouts visited are places, not ten additional independent recordings.

Sensor membership varies: some recordings have one Velodyne, omit rear/lateral imagery or omit RTK, and radar appears only in April 2019. Check each download-table row.

Only paired Velodynes have PPS phase locking; other streams use approximate timestamp alignment. Interference/shadow filtering and early timestamp offsets affect processing.

The front XB3 left/right stereo pair is documented by the playback example; center-channel/calibration alternatives do not establish a uniformly released extra image stream. Rear stereo and lateral imagery are subset-dependent.

RTK is partial and supplies position without independently established full attitude or numerical accuracy. The legal 50 km/h limit is not an observed maximum speed.

Later challenge annotations apply to selected scenarios. They do not establish uniform human annotation across the full long-term and roundabout collection.

Cameras

Camera 1

Model
Bumblebee XB3
Setup
Stereo
Count
1
Effective cameras
2
Modality
Not Reported
Resolution
Not reported
Rate
8 Hz
Shutter
Global
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
One front stereo system; the official playback example uses the left/right pair. Calibration also describes a center channel; additional delivered XB3 imager selections/cadences remain unverified.

Camera 2

Model
Bumblebee2
Setup
Stereo
Count
1
Effective cameras
2
Modality
Rgb
Resolution
Not reported
Rate
8 Hz
Shutter
Global
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
One rear stereo system; official playback debayers left/right images. Absent from the first two long-term recordings and the January 31 snow recording.

Camera 3

Model
Pixelink PL-B742F
Setup
Fisheye
Count
2
Effective cameras
2
Modality
Not Reported
Resolution
Not reported
Rate
15 Hz
Shutter
Global
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Two lateral fisheye devices, present only in the later recordings. Exact delivered modality and dimensions remain unverified.

IMUs

Xsens vehicle IMU

Model
Xsens MTi-28A53G25
Count
1
Accel / gyro
100 / 100 Hz

GNSS

Magellan ProFlex 500

Model or name
Magellan ProFlex 500
Count
1
Rate
15 Hz
GNSS type
RTK
Position output
Available
Velocity output
Not reported
Heading output
Not reported

LiDAR

Velodyne HDL-32E

Model or name
Velodyne HDL-32E
Count
2
Dimensions
3
Rate
10 Hz
Channels
32
Range
Not reported

ibeo LUX 4L

Model or name
ibeo LUX 4L
Count
1
Dimensions
3
Rate
12.5 Hz
Channels
4
Range
Not reported

SICK LMS100-10000

Model or name
SICK LMS100-10000
Count
1
Dimensions
2
Rate
50 Hz
Channels
1
Range
Not reported

Radar

Continental ARS 308

Count
1
Released data
Not reported
Frame rate
25 Hz
Doppler velocity
Not reported
Elevation angle
Not reported
Configured range
Not reported
Field of view
Not reported
Notes
Listed only for the April 2019 long-term and roundabout recordings, not the whole collection.

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Not reported
Format
Not reported
Class count
Not reported
Semantic segmentation Not reported
Instance segmentation Not reported
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
yan2019utbmrobocar

BibTeX

@misc{yan2019utbmrobocar,
  author = {{Zhi Yan} and {Li Sun} and {Tomáš Krajník} and {Yassine Ruichek}},
  title = {EU Long-term Dataset with Multiple Sensors for Autonomous Driving},
  year = {2019},
  eprint = {1909.03330},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1909.03330v3}
}

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