---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- multi-robot
- manipulation
- bone-picking
configs:
- config_name: default
  data_files: data/*/*.parquet
---

# Bone to Pick - Combined Dataset (10_08 + 10_09)

This dataset is a merged combination of two Bone to Pick datasets from Hugging Face:
- [oordonez/Bone_to_Pick_10_08](https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_08)
- [oordonez/Bone_to_Pick_10_09](https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_09)

## Dataset Description

This dataset was created using [LeRobot](https://github.com/huggingface/lerobot) and contains bi-manual robot manipulation data for a bone picking task. The dataset combines 20 episodes (10 from each original dataset) with updated episode numbering to avoid conflicts.

### Key Features:
- **Total Episodes**: 20 (episodes 0-19)
- **Total Frames**: 7,788 (after dead time removal)
- **Total Videos**: 60 (3 camera views × 20 episodes)
- **Robot Type**: Dual-arm manipulation (white + blue follower arms)
- **Task**: Grasp the blue bone and place it inside the box

### Camera Views:
1. `observation.images.my_blue_follower_arm_front` (640×480, H.264)
2. `observation.images.my_white_follower_arm_front` (640×480, H.264)  
3. `observation.images.my_white_follower_arm_global_top` (1280×720, H.264)

## Dataset Structure

### Data Format:
- **Action Space**: 12-dimensional float32 arrays
  - 6 joints for white follower arm
  - 6 joints for blue follower arm
- **Observation Space**: 12-dimensional float32 arrays (same as action)
- **Timestamps**: float32 timestamps
- **Frame Indices**: int64 frame numbers within each episode
- **Episode Indices**: int64 episode numbers (0-19)

### Joint Names:
**White Follower Arm:**
- `my_white_follower_arm_shoulder_pan.pos`
- `my_white_follower_arm_shoulder_lift.pos`
- `my_white_follower_arm_elbow_flex.pos`
- `my_white_follower_arm_wrist_flex.pos`
- `my_white_follower_arm_wrist_roll.pos`
- `my_white_follower_arm_gripper.pos`

**Blue Follower Arm:**
- `my_blue_follower_arm_shoulder_pan.pos`
- `my_blue_follower_arm_shoulder_lift.pos`
- `my_blue_follower_arm_elbow_flex.pos`
- `my_blue_follower_arm_wrist_flex.pos`
- `my_blue_follower_arm_wrist_roll.pos`
- `my_blue_follower_arm_gripper.pos`

## Processing Details

### Dead Time Removal:
- Applied velocity threshold of 0.0001 for joint movement detection
- Removed 2+ seconds of stationary data at episode ends
- Total frames removed: 1,496 frames across all episodes

### Video Processing:
- Converted all videos from AV1 to H.264 codec for browser compatibility
- Maintained original frame rates (30 FPS)
- Preserved video quality and aspect ratios

### Episode Renumbering:
- Original dataset 10_08: episodes 0-9 → merged episodes 0-9
- Original dataset 10_09: episodes 0-9 → merged episodes 10-19
- All metadata updated to reflect new episode numbering

## Dataset Viewer Information

### What You'll See in the Hugging Face Dataset Viewer:

#### **📊 Data Columns:**
- **`action`**: 12-element array containing joint positions for both robot arms
- **`observation.state`**: 12-element array containing current joint states  
- **`timestamp`**: float32 timestamp for each frame
- **`frame_index`**: int64 frame number within each episode
- **`episode_index`**: int64 episode number (0-19)
- **`index`**: int64 global sample index
- **`task_index`**: int64 task identifier

#### **🤖 Joint Mapping (12 elements in action/observation arrays):**
**Indices 0-5: White Follower Arm**
- Index 0: `my_white_follower_arm_shoulder_pan.pos`
- Index 1: `my_white_follower_arm_shoulder_lift.pos`
- Index 2: `my_white_follower_arm_elbow_flex.pos`
- Index 3: `my_white_follower_arm_wrist_flex.pos`
- Index 4: `my_white_follower_arm_wrist_roll.pos`
- Index 5: `my_white_follower_arm_gripper.pos`

**Indices 6-11: Blue Follower Arm**
- Index 6: `my_blue_follower_arm_shoulder_pan.pos`
- Index 7: `my_blue_follower_arm_shoulder_lift.pos`
- Index 8: `my_blue_follower_arm_elbow_flex.pos`
- Index 9: `my_blue_follower_arm_wrist_flex.pos`
- Index 10: `my_blue_follower_arm_wrist_roll.pos`
- Index 11: `my_blue_follower_arm_gripper.pos`

#### **🎥 Video Files:**
- **60 total videos** (3 camera views × 20 episodes)
- All videos are in H.264 codec for browser compatibility
- Videos are stored in the `videos/` directory

## Usage

### Loading the Dataset:
```python
from datasets import load_from_disk

# Load the dataset
dataset = load_from_disk('merged_bone_to_pick_combined_hf_fixed')

# Access a sample
sample = dataset[0]
print(f"Action: {sample['action']}")
print(f"Observation: {sample['observation.state']}")
print(f"Episode: {sample['episode_index']}")

# Access joint values by index
action = sample['action']
white_arm_joints = action[:6]  # First 6 elements
blue_arm_joints = action[6:]   # Last 6 elements
```

### Accessing Videos:
```python
# Videos are stored in the videos/ directory
# Each episode has 3 camera views:
# - observation.images.my_blue_follower_arm_front/episode_XXXXXX.mp4
# - observation.images.my_white_follower_arm_front/episode_XXXXXX.mp4  
# - observation.images.my_white_follower_arm_global_top/episode_XXXXXX.mp4
```

## Dataset Statistics

| Metric | Value |
|--------|-------|
| Total Episodes | 20 |
| Total Frames | 7,788 |
| Total Videos | 60 |
| Average Frames per Episode | 389.4 |
| Video Codec | H.264 |
| Frame Rate | 30 FPS |
| Data Format | LeRobot v2.1 |

## Citation

**BibTeX:**
```bibtex
@dataset{merged_bone_to_pick_combined,
  title={Bone to Pick - Combined Dataset (10_08 + 10_09)},
  author={oordonez},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_08},
  url={https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_09}
}
```

## License

This dataset is released under the Apache 2.0 License.

## Acknowledgments

- Original datasets: [oordonez/Bone_to_Pick_10_08](https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_08) and [oordonez/Bone_to_Pick_10_09](https://huggingface.co/datasets/oordonez/Bone_to_Pick_10_09)
- Built with [LeRobot](https://github.com/huggingface/lerobot)
- Merged and processed for improved usability and browser compatibility