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---
license: cc-by-nc-4.0
task_categories:
- robotics
---
# MCAP Robotics Dataset Collection
This repository contains a comprehensive collection of robotics datasets converted to the MCAP format, specifically designed for SLAM (Simultaneous Localization and Mapping) and multi-modal sensor fusion research.
## Dataset Overview
Our collection includes three major robotics datasets:
### 🚀 [FAST-LIVO Dataset](./FAST-LIVO/)
- **Focus**: LiDAR-Inertial-Visual Odometry systems
- **Scenarios**: University campus, LiDAR degenerate cases, visual challenges
- **Applications**: Algorithm robustness testing, multi-modal fusion
### 🌈 [R3LIVE Dataset](./R3LIVE/)
- **Focus**: Real-time Radiance Reconstruction and RGB-colored mapping
- **Scenarios**: HKU campus sequences, indoor buildings, outdoor environments
- **Applications**: Photorealistic 3D reconstruction, real-time dense mapping
### 🛰️ [MARS-LVIG Dataset](./mars_lvig/)
- **Focus**: Multi-sensor SLAM with LiDAR-Visual-Inertial-GNSS fusion
- **Scenarios**: Diverse outdoor environments with GNSS integration
- **Applications**: Robust state estimation, multi-sensor fusion, GNSS-aided navigation
## Key Features
- **Standardized Format**: All datasets converted to MCAP for consistent processing
- **Multi-modal Data**: Synchronized LiDAR, IMU, and camera measurements
- **Diverse Scenarios**: Indoor, outdoor, and challenging environmental conditions
- **Research Ready**: Optimized for SLAM algorithm development and evaluation
## File Format
- **`.mcap`**: Main data files containing synchronized sensor measurements (LiDAR, IMU, camera data)
- **`metadata.yaml`**: Configuration and metadata files describing recording parameters and sensor specifications
## Usage
These MCAP files can be processed using standard robotics tools and libraries that support the MCAP format for multi-modal sensor data analysis and SLAM algorithm evaluation.
### Recommended Tools
- [ros2mcap](https://github.com/DapengFeng/ros2mcap) - ROS 1 MCAP support
- [MCAP CLI](https://mcap.dev/guides/cli) - Command-line tools for MCAP manipulation
- [Foxglove Studio](https://foxglove.dev/) - Visualization and analysis platform
- [ROS 2](https://docs.ros.org/en/humble/Concepts/About-ROS-Interfaces.html) - Robot Operating System with MCAP support
## Getting Started
1. **Browse datasets**: Explore individual dataset folders for specific scenarios
2. **Read metadata**: Check `metadata.yaml` files for sensor specifications
3. **Load MCAP files**: Use your preferred robotics framework or MCAP tools
4. **Analyze data**: Process synchronized sensor streams for your research
## Applications
This dataset collection is ideal for:
- SLAM algorithm development and benchmarking
- Multi-sensor fusion research
- Real-time mapping and localization studies
- Sensor calibration and synchronization validation
- Computer vision and robotics education
## License
This dataset collection is licensed under **CC-BY-NC-4.0** (Creative Commons Attribution-NonCommercial 4.0 International). This means you can use, share, and adapt the material for non-commercial purposes with proper attribution.
## Contributing
We welcome contributions of additional datasets or improvements to existing ones. Please ensure all data follows our MCAP formatting standards and includes appropriate metadata.
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