rtk-slam-dataset / README.md
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metadata
language:
  - en
license: cc-by-4.0
size_categories:
  - 100G<n<1T
task_categories:
  - robotics
pretty_name: RTK-SLAM Dataset
tags:
  - slam
  - rtk
  - lidar
  - imu
  - gnss
  - localization
  - georeferencing
  - ros

RTK-SLAM Dataset

An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments

Wei Zhang, Vincent Ress, David Skuddis, Uwe Soergel, Norbert Haala
Institute for Photogrammetry and Geoinformatics, University of Stuttgart, Germany

[Project Page] | [Paper] | [Code]


Overview

This dataset is designed for evaluating the absolute global positioning accuracy of RTK-SLAM systems in GNSS-degraded and GNSS-denied environments. A key design principle is that the RTK receiver is used exclusively as a system input, while ground truth is established independently via a geodetic total station. This separation is absent from all existing datasets.

Standard SLAM benchmarks evaluate accuracy using SE(3)-aligned ATE, which absorbs global drift and can underestimate absolute errors by up to 76%. This dataset enables direct evaluation without SE(3) alignment.


Sensor Platform

A handheld device comprising:

Sensor Model Rate
LiDAR + IMU Livox MID360 10 Hz / 200 Hz
Camera 2 MP global shutter 20 Hz
GNSS receiver Unicore UM980 10 Hz

RTK corrections provided by the German SAPOS service (centimeter-level accuracy under open sky).


Sequences

Sequence Duration Length RTK Fix Checkpoints Type
Stadtgarten Seq. 1 26 min 42 s 1.04 km 54% 36 Outdoor park
Stadtgarten Seq. 2 14 min 36 s 0.46 km 40% 19 Outdoor park
Construction Hall Seq. 1 12 min 21 s 0.48 km 25% 16 Outdoor + Indoor
Construction Hall Seq. 2 9 min 59 s 0.39 km 23% 16 Outdoor + Indoor

Stadtgarten: Public park in Stuttgart with open-sky areas, tree cover, building obstruction, and a 30 m GNSS-denied underpass.

Construction Hall: Large construction site (IntCDC, University of Stuttgart) with short outdoor segments and a GNSS-denied indoor hall spanning 400+ s of travel.


Repository Structure

rtk-slam-dataset/
├── ros1/                          # ROS1 (.bag) format
│   ├── construction_seq1.bag
│   ├── construction_seq2.bag
│   ├── stadtgarten_seq1.bag
│   └── stadtgarten_seq2.bag
├── ros2/                          # ROS2 (.db3) format
│   ├── construction_seq1/
│   ├── construction_seq2/
│   ├── stadtgarten_seq1/
│   └── stadtgarten_seq2/
└── euroc/                         # Extended EuRoC format (compatible with OKVIS2-X)
    ├── construction_seq1_euroc.zip
    ├── construction_seq2_euroc.zip
    ├── stadtgarten_seq1_euroc.zip
    └── stadtgarten_seq2_euroc.zip

ROS Topics

Topic Type Rate
/livox/lidar livox_ros_driver/CustomMsg 10 Hz
/livox/points sensor_msgs/PointCloud2 10 Hz
/livox/imu sensor_msgs/Imu 200 Hz
/camera/image_raw/compressed sensor_msgs/CompressedImage 20 Hz
/gnss/fix sensor_msgs/NavSatFix 10 Hz

Note on camera timestamps: The camera has a hardware trigger delay of −20.6 ms relative to the IMU clock (estimated by Kalibr). This offset is already compensated in all released formats — camera image timestamps in the ROS bags and EuRoC files reflect the corrected capture time. No additional time shift is needed when using this data.


Privacy

All camera images were anonymized prior to release by blurring human faces using deface.


Citation

@article{zhang2025rtkslam,
  title   = {An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments},
  author  = {Zhang, Wei and Ress, Vincent and Skuddis, David and Soergel, Uwe and Haala, Norbert},
  journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences},
  year    = {2025},
}

License

This dataset is released under CC BY 4.0.