AutoMap Dataset: High-Resolution Urban Mapping

The AutoMap Dataset is a high-fidelity multi-modal collection designed for urban mapping and autonomous navigation research. It features synchronized high-resolution imagery and dense point clouds from automotive-grade solid-state LiDARs, providing a robust benchmark for SLAM, 3D reconstruction, and sensor fusion.

Table of Contents

1. Dataset Overview

2. Hardware Setup & Mounting

3. Calibration & Synchronization

4. Collection Context

5. Directory Structure

6. Coordinate Systems

7. Usage & Getting Started

8. Access & Licensing

1. Dataset Overview

• Summary: An urban dataset captured with high-resolution Basler cameras and dense Livox HAP solid-state LiDARs.

• Total Duration: 29 Minutes.

• Environment: Urban / Inner City (Hannover, Germany).

• Weather: Sunny.

• Total Data Size: 1.13 TB.

2. Hardware Setup & Mounting

The data was collected using a custom mobile mapping platform mounted on an Opel Vivaro van.

CAD Mockup of the Sensors as Mounted on the Test Vehicle

Simulated FoV Coverage of the Mounted Sensors. Green: LiDAR Coverage. Purple: Camera Coverage

Front and Side View of the Mounted MSS During The Dataset Collection

Sensor Specifications

• LiDAR
  • Model: 2 x Livox HAP (Solid-State)
  • Configuration: Left/Right Pair
  • Key Specs: 120° FOV, Dense non-repetitive scanning
• Camera
  • Model: 2 x Basler a2A2840-67g5cBAS
  • Configuration: Left/Right Pair
  • Key Specs: 8.1 MP, 2840 x 2840 resolution
• INS/GNSS
  • Model: OxTS AV200
  • Configuration: Roof-mounted
  • Key Specs: Dual Antenna, RTK/PPK capable

Mounting & Coverage

The sensors are mounted in a rigid frame atop the Opel Vivaro, optimized for wide area coverage, and minimum overlap between the solid-state LiDAR FOVs and the high-resolution cameras.

3. Calibration & Synchronization

Precision is maintained through rigorous calibration routines and sub-millisecond hardware synchronization.

Calibration Procedure

• Intrinsic (Camera): Checkerboard-based calibration using the ROS Calibration Toolbox. Parameters are stored in calibration.json.

• Intrinsic (IMU): Allan Variance analysis via the ROS Toolbox.

• Extrinsic (Sensor-to-Sensor):

• Camera-LiDAR: Initial extrinsic parameters for left and right pairs were estimated using ACSC toolbox.

• Camera-IMU: The extrinsic transformation between the Left Camera and the INS IMU was estimated using the Kalibr toolbox.

• Global Alignment: The two sensor pairs (LiDAR-Camera pairs) were ultimately calibrated and aligned using the cameras with Ground Control Points (GCPs) in a known external reference frame to ensure absolute spatial accuracy.

• *Transformations: All final extrinsic matrices (T_sensor_to_left_lidar) derived from this multi-step process are provided in calibration.json.

Synchronization & Status

• Grandmaster Clock: All hardware is synchronized to GPS time.

• Protocols:

• PTP: Used for synchronization between INS and Camera.

• gPTP: Used for LiDAR synchronization.

• Data Status:

• Images: Provided as Raw (Bayer RG8) lossless .png format .

• LiDAR: Provided as raw and undistorted .pcd (corrected via internal LiDAR IMUs).

• Navigation: INS data is PPK-processed at 100 Hz, including GNSS and raw IMU logs in a .csv format.

4. Collection Context

Route of the Vehicle During the Dataset Collection

Location: Hannover, Germany

The dataset was recorded in the inner city of Hannover. The trajectory covers a mix of narrow and wide European streets.

Conditions

• Time of Day: Afternoon.

• Traffic: Variable density featuring multiple "stop-and-go" scenarios, typical for mid-day urban environments.

• Complexity: Includes interactions with pedestrians, cyclists, and trams.

5. Directory Structure

6. Coordinate Systems

Local Sensor Frames: Each sensor's data (images, point clouds, IMU) is provided in its respective local coordinate frame. To transform data between sensors, refer to the transformation matrices in calibration.json.

• Reference Frame: The Left LiDAR serves as the primary coordinate reference for the sensor rig.

• Global References:

  • Lateral: ETRS89 / UTM zone 32N (EPSG:25832).

  • Vertical: DHHN2016 (German Main Height Network / EPSG:7837).

7. Usage & Getting Started

To Be Released

8. Licensing

License

This dataset is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License. You are free to share and adapt the material for academic and research purposes, as long as appropriate credit is given and the dataset is not used for commercial purposes.