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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- robotics |
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--- |
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# MCAP Robotics Dataset Collection |
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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. |
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## Dataset Overview |
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Our collection includes three major robotics datasets: |
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### 🚀 [FAST-LIVO Dataset](./FAST-LIVO/) |
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- **Focus**: LiDAR-Inertial-Visual Odometry systems |
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- **Scenarios**: University campus, LiDAR degenerate cases, visual challenges |
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- **Applications**: Algorithm robustness testing, multi-modal fusion |
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### 🌈 [R3LIVE Dataset](./R3LIVE/) |
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- **Focus**: Real-time Radiance Reconstruction and RGB-colored mapping |
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- **Scenarios**: HKU campus sequences, indoor buildings, outdoor environments |
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- **Applications**: Photorealistic 3D reconstruction, real-time dense mapping |
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### 🛰️ [MARS-LVIG Dataset](./mars_lvig/) |
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- **Focus**: Multi-sensor SLAM with LiDAR-Visual-Inertial-GNSS fusion |
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- **Scenarios**: Diverse outdoor environments with GNSS integration |
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- **Applications**: Robust state estimation, multi-sensor fusion, GNSS-aided navigation |
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## Key Features |
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- **Standardized Format**: All datasets converted to MCAP for consistent processing |
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- **Multi-modal Data**: Synchronized LiDAR, IMU, and camera measurements |
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- **Diverse Scenarios**: Indoor, outdoor, and challenging environmental conditions |
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- **Research Ready**: Optimized for SLAM algorithm development and evaluation |
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## File Format |
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- **`.mcap`**: Main data files containing synchronized sensor measurements (LiDAR, IMU, camera data) |
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- **`metadata.yaml`**: Configuration and metadata files describing recording parameters and sensor specifications |
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## Usage |
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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. |
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### Recommended Tools |
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- [ros2mcap](https://github.com/DapengFeng/ros2mcap) - ROS 1 MCAP support |
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- [MCAP CLI](https://mcap.dev/guides/cli) - Command-line tools for MCAP manipulation |
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- [Foxglove Studio](https://foxglove.dev/) - Visualization and analysis platform |
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- [ROS 2](https://docs.ros.org/en/humble/Concepts/About-ROS-Interfaces.html) - Robot Operating System with MCAP support |
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## Getting Started |
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1. **Browse datasets**: Explore individual dataset folders for specific scenarios |
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2. **Read metadata**: Check `metadata.yaml` files for sensor specifications |
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3. **Load MCAP files**: Use your preferred robotics framework or MCAP tools |
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4. **Analyze data**: Process synchronized sensor streams for your research |
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## Applications |
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This dataset collection is ideal for: |
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- SLAM algorithm development and benchmarking |
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- Multi-sensor fusion research |
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- Real-time mapping and localization studies |
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- Sensor calibration and synchronization validation |
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- Computer vision and robotics education |
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## License |
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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. |
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## Contributing |
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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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