List of Datasets

UGV, Quadruped

EnvoDat

SLAM; semantic perception

Wheeled and quadruped recordings across indoor, forest/street and underground degradation scenarios.

Metadata: Complete Metadata source documented Released 2024

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

Quick facts

Vehicle type
UGV, Quadruped
Environment
Indoor, Outdoor
Data origin
Real-world
Sensor count
5
Ground truth
Available
Calibration
Not reported
Annotations
Available

Sensor overview

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

Cameras

3 reported

IMUs

1 reported

GNSS

Not reported

LiDAR

1 reported

Radar

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 LiDAR SLAM GLIM pseudo-ground truth Not reported Not reported Unknown 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.
Derived
Reference notes
Per-scene input LiDAR/inertial constraints; map overlays are not independent pose-error certification.

Calibration and synchronization

Reported calibration level, reproducibility signals, and supporting notes.

Level
Not reported
Processed parameters
Not reported
Raw calibration data
Not reported
Calibration targets
Not reported

Calibration data

Calibration reproducibility details are not reported.

Notes

Details delegated to project site; parameters/raw session release not established by PDF.

Known or intentional limitations

Reported constraints and characteristics to check before using the dataset.

Twenty-six sequences cover thirteen scenes. Point clouds, LiDAR-derived image layers, selected image frames and annotation polygons use different counting units; ten modalities do not mean ten physical sensors.

GLIM pseudo-trajectories and reconstructed maps reuse LiDAR/inertial inputs. Map overlays and cloud-scale comparisons do not certify independent pose accuracy or complete timestamp coverage.

The paper describes approximate ROS pairing with a few seconds of accuracy. Achieved alignment uncertainty remains unknown and is not converted into a millisecond synchronization guarantee.

Fine-grained polygon labels cover selected images. Calibration procedures do not by themselves establish complete downloadable raw sessions; scene download links use the author data-request form.

Cameras

Camera 1

Model
Intel RealSense D435i
Setup
Rgbd
Count
1
Effective cameras
2
Modality
Rgbd
Resolution
1920 x 1080
Rate
30 Hz
Shutter
Not Reported
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Documented RGB 1920x1080 and depth 1280x720 at 30 Hz. Platform-specific inventory differs.

Camera 2

Model
ELP4K
Setup
Mono
Count
1
Effective cameras
1
Modality
Rgb
Resolution
Not reported
Rate
30 Hz
Shutter
Not Reported
Lens type
Not Reported
HFOV
Not reported
VFOV
Not reported
Notes
Indoor subset only; exact export resolution not established.

IMUs

Released inertial measurements

Model
Not reported
Count
1
Accel / gyro
Not reported

GNSS

Not reported

LiDAR

Ouster (exact model unknown)

Model or name
Ouster (exact model unknown)
Count
1
Dimensions
3
Rate
10 Hz
Channels
32
Range
Not reported

Radar

Not reported

Additional sensors

Not reported

Annotations

Reported annotation availability and task support.

Availability
Available
Format
Layered RGB polygons exported JSON/XML/TXT/CSV; selected frames, not all images.
Class count
82
Semantic segmentation Available
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
nwankwo2025envodat

BibTeX

@INPROCEEDINGS{nwankwo2025envodat,
  author={Nwankwo, Linus and Ellensohn, Björn and Dave, Vedant and Hofer, Peter and Forstner, Jan and Villneuve, Marlene and Galler, Robert and Rueckert, Elmar},
  booktitle={2025 IEEE International Conference on Robotics and Automation (ICRA)}, 
  title={EnvoDat: A Large-Scale Multisensory Dataset for Robotic Spatial Awareness and Semantic Reasoning in Heterogeneous Environments}, 
  year={2025},
  volume={},
  number={},
  pages={153-160},
  keywords={Simultaneous localization and mapping;Annotations;Heuristic algorithms;Supervised learning;Semantics;Benchmark testing;Cognition;Spatial databases;Robustness;Sensors},
  doi={10.1109/ICRA55743.2025.11127594}}

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