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feat(dataset): add FAST-LIVO dataset with metadata and README

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Introduce the FAST-LIVO dataset for LiDAR-Inertial-Visual Odometry research. Includes MCAP files for scenarios such as urban campus
environments, LiDAR degenerate conditions, and visual challenges.

FAST-LIVO/LiDAR_Degenerate/LiDAR_Degenerate_0.mcap ADDED
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FAST-LIVO/README.md ADDED
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+ # [FAST-LIVO Dataset](https://github.com/hku-mars/FAST-LIVO)
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+
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+ This dataset contains MCAP files for robotics research, specifically focused on LiDAR-Inertial-Visual Odometry (LIVO) systems.
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+
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+ ## Dataset Structure
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+
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+ The dataset is organized into the following scenarios:
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+
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+ ### 📍 **hku1** & **hku2**
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+ University campus sequences recorded at Hong Kong University, providing urban outdoor environments with mixed static and dynamic objects.
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+
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+ ### 🔍 **LiDAR_Degenerate**
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+ Challenging scenarios where LiDAR measurements may be degraded or provide limited geometric constraints, useful for testing algorithm robustness.
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+
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+ ### 👁️ **Visual_Challenge**
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+ Sequences with challenging visual conditions such as lighting changes, motion blur, or low-texture environments that stress visual odometry components.
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README.md CHANGED
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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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  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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+
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+ ## File Format
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+
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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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+
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+ ## Usage
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+
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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.