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+ # πŸ€– Robot Data Collection Guide
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+ A practical guide for collecting clean, diverse, and meaningful datasets to train and evaluate robot models.
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+ ---
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+ ## πŸ“Œ Why This Matters
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+ High-quality data is the foundation for:
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+ - Behavior cloning
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+ - Multi-robot coordination
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+ - Sim-to-real transfer
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+ - Sensor fusion and modeling
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+
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+ ---
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+ ## πŸ“‚ What's Inside
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+ - βœ… Types of data to collect (images, joint states, LiDAR, IMU)
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+ - βœ… How to record multi-modal data (ROS 2 bag files)
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+ - βœ… Labeling methods (manual, semi-auto)
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+ - βœ… Data cleaning and preprocessing
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+ - βœ… Storage & formats: `.db3`, `.csv`, `JSON`
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+
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+ ---
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+ ## πŸ›  Tools You Can Use
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+ | Tool | Purpose |
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+ |-----------------|----------------------------------|
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+ | ROS 2 | Real-time data collection |
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+ | `rosbag2_py` | Python access to .db3 files |
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+ | DB Browser | Inspect SQLite `.db3` bags |
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+ | OpenCV / PIL | Preprocess visual data |
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+ | Pandas | Work with CSVs |
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+ | Hugging Face | Store models/datasets online |
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+ ---
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+ ## πŸ“¦ Example Commands
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+ ```bash
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+ # Record robot states + camera stream
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+ ros2 bag record /joint_states /camera/image_raw /tf