vla-model/construction-multimodel-dataset
Construction Traversability Dataset A construction-site RGB semantic segmentation dataset developed for research on terrain understanding, traversability estimation, and multimodal RGB–LiDAR perception for mobile robots. Overview This dataset contains RGB images and pixel-wise semantic segmentation masks collected in construction-site environments. The dataset is intended to support research on construction-site scene understanding and traversability-aware robot… See the full description on the dataset page: https://huggingface.co/datasets/vla-model/construction-multimodel-dataset.
Construction Traversability Dataset
A construction-site RGB semantic segmentation dataset developed for research on terrain understanding, traversability estimation, and multimodal RGB–LiDAR perception for mobile robots.
Overview
This dataset contains RGB images and pixel-wise semantic segmentation masks collected in construction-site environments. The dataset is intended to support research on construction-site scene understanding and traversability-aware robot perception.
The release also includes the camera/LiDAR calibration used for RGB–LiDAR projection and the fine-tuned semantic segmentation model used in the associated research.
Dataset Contents
construction-traversability-dataset/
├── README.md
├── LICENSE
├── dataset.yaml
│
├── images/
│ ├── train/
│ └── val/
│
├── masks/
│ ├── train/
│ └── val/
│
├── calibration/
│ ├── camera_intrinsics.yaml
│ └── lidar_camera_extrinsics.yaml
│
├── model/
│ └── model_config.yaml
│ └── yolo26_sem_construction.ptRGB Images
RGB images are provided under:
images/train/images/val/
Semantic Masks
Each RGB image has a corresponding pixel-wise semantic segmentation mask under the masks/ directory.
The mask uses integer class IDs, with the class definitions given below. The RGB image and mask use corresponding filenames.
This is a pixel-wise semantic segmentation representation rather than COCO polygon/RLE annotation format.
Semantic Classes
The dataset uses the following 28-class construction-site taxonomy:
The class IDs correspond to the dataset taxonomy used by the semantic segmentation and RGB–LiDAR fusion pipeline.
Dataset Configuration
dataset.yaml contains the train/validation paths and class names used by the training pipeline.
Example:
path: .
train: images/train
val: images/val
names:
0: animal
1: building
...The repository's dataset.yaml should be treated as the authoritative training configuration.
Camera and LiDAR Calibration
The calibration/ directory contains the sensor parameters used by the RGB–LiDAR projection pipeline.
Camera Intrinsics
calibration/camera_intrinsics.yaml contains the OAK-D RGB camera intrinsic matrix used for projection.
The projection code uses a 640 × 480 image size and:
fx = 513.8645629882812
fy = 513.7389526367188
cx = 316.9952392578125
cy = 247.48223876953125The supplied calibration file does not specify distortion coefficients.
LiDAR–Camera Extrinsics
calibration/lidar_camera_extrinsics.yaml contains the transforms used to relate the Livox LiDAR and OAK-D RGB camera frames through the base_footprint frame, including the optical-frame correction used by the fusion pipeline.
These parameters document the transforms used by the released processing pipeline. They should not be interpreted as an independently certified metrology calibration unless otherwise stated.
Fine-Tuned Semantic Segmentation Model
The model/ directory contains the fine-tuned semantic segmentation model used for the construction-site taxonomy.
The model is based on the YOLO26 semantic segmentation architecture and is fine-tuned for the 28 construction-site classes listed above.
The model is provided to facilitate reproducibility of the semantic segmentation and RGB–LiDAR fusion experiments.
Raw ROS 2 Data
The complete ROS 2 recordings used during data collection may be released separately because of their large file size.
Raw ROS bag repository: https://huggingface.co/datasets/vla-model/construction-rosbags The raw recordings are intended to provide the original sensor data and timestamps needed for reproduction and further research.
Distinct rgb and lidar frames in sync
Similar to rosbags, distinct rbg images and lidar frame can be downloaded separately from the following link.
Sync rbg and lidar frames repository: https://huggingface.co/datasets/vla-model/construction-syn-data
Data Format
The released annotated data is organized as paired RGB images and pixel-wise semantic masks.
This format is intentionally kept simple so that it can be used directly by semantic segmentation pipelines without requiring conversion from COCO polygon/RLE annotations.
Researchers who require another annotation format may convert the masks to their preferred representation.
Intended Use
This dataset is released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Commercial use is not permitted. See LICENSE for the full license terms.
Possible applications include:
- construction-site semantic segmentation
- terrain and traversability perception
- RGB–LiDAR fusion
- mobile robot navigation
- construction-site scene understanding
- semantic costmap generation
- multimodal robotic perception
License
The dataset and associated materials in this repository are released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.
Commercial use is not permitted under this license.
See `LICENSE` for the full license text.
License information: https://creativecommons.org/licenses/by-nc/4.0/
Disclaimer
The dataset is provided for research purposes. No guarantee is made regarding the completeness, accuracy, or suitability of the data for a particular application. Users are responsible for validating the data before deploying models or systems based on it in real-world environments.