| --- |
| license: cc-by-4.0 |
| task_categories: |
| - robotics |
| tags: |
| - robotics |
| - lidar |
| - traversability |
| - off-road |
| - construction |
| - point-cloud |
| - autonomous-navigation |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Construction-Site Multimodal Dataset (CMAD) |
|
|
| Real-world RGB + LiDAR + pose data collected on a live construction site with a custom ground-robot sensor rig. Three sequences, **16,401 synchronized frames (~78 minutes)** of camera, LiDAR, and 6-DoF odometry, laid out in a directory/loader convention compatible with the public [RELLIS-3D](https://unmannedlab.github.io/research/RELLIS-3D) benchmark, so existing off-road traversability-estimation tooling built around that convention can consume it with only a root-path change. |
|
|
| This dataset was collected to support research on self-supervised traversability estimation in tight, unstructured, real-world spaces — construction sites in particular, where narrow corridors, active equipment, and LiDAR-hazardous surfaces (open trenches, standing water, reflective debris) are common. Collection intentionally includes routes an operator judged difficult or borderline-traversable, not only easy/typical driving. |
|
|
| ## Sensor rig |
|
|
| - RGB camera, 640×480, intrinsics `fx≈399.7, fy≈399.8, cx≈330.4, cy≈197.7`. |
| - Solid-state LiDAR, extrinsically calibrated against the rig's static TF tree. |
|
|
| ## Dataset structure |
|
|
| | Sequence | Frames | Duration | Notes | |
| |---|---|---|---| |
| | `00000` | 9,767 | ≈47.0 min | | |
| | `00001` | 3,100 | ≈14.6 min | | |
| | `00002` | 3,534 | ≈16.5 min | odometry diverges in the final ~3% of frames — see Known Issues below | |
| | **Total** | **16,401** | **≈78.1 min** | ≈3.5 Hz camera/LiDAR rate | |
|
|
| Each sequence directory contains: |
|
|
| ``` |
| <seq>/ |
| ├── calib.txt |
| ├── camera_info.txt |
| ├── camera_times.txt |
| ├── frame_times.txt |
| ├── poses.txt # per-frame 6-DoF pose, row-major flattened 3x4 [R|t] |
| ├── imu.npy |
| ├── sync_report.csv |
| ├── pylon_camera_node/ # RGB images, one per frame |
| └── os1_cloud_node_kitti_bin/ # LiDAR point clouds, one per frame (KITTI .bin format) |
| ``` |
|
|
| ## Known issues |
|
|
| Sequence `00002`'s onboard LiDAR odometry is reliable for the great majority of the sequence but diverges sharply in its final ~3% of frames (single-frame position jumps of tens of meters, consistent with an odometry tracking failure). Reported here transparently rather than filtered out — if using pose data from this sequence, exclude the tail or verify pose continuity before relying on it. |
|
|
| ## License |
|
|
| This dataset is released under the **Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)** license. |
|
|
| The recordings may be used, shared, and adapted for non-commercial purposes with appropriate attribution. Commercial use is not permitted without separate permission from the dataset authors. |
|
|
