README.md

---
license: cc-by-4.0
task_categories:
  - robotics
language:
  - en
tags:
  - robotics
  - manipulation
  - lerobot
  - humanoid
  - reachy2
  - pick-and-place
  - simulation
  - mujoco
  - gr00t
  - nvidia
  - physical-ai
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: "data/**/*.parquet"
---

# NOVA Dataset - Reachy 2 Pick-and-Place Demonstrations

<p align="center">
  <img src="https://img.shields.io/badge/Format-LeRobot%20v2.1-FFD21E?style=for-the-badge&logo=huggingface" alt="LeRobot v2.1"/>
  <img src="https://img.shields.io/badge/Episodes-100-blue?style=for-the-badge" alt="100 Episodes"/>
  <img src="https://img.shields.io/badge/Robot-Reachy%202-0066CC?style=for-the-badge" alt="Reachy 2"/>
</p>

Expert demonstration dataset for training vision-language-action models on [Pollen Robotics' Reachy 2](https://www.pollen-robotics.com/reachy/) humanoid robot. Collected in MuJoCo simulation with domain randomization.

## Dataset Description

This dataset contains **100 episodes** of pick-and-place manipulation tasks, designed for fine-tuning NVIDIA GR00T N1.6 or other imitation learning policies.

### Key Features

| Feature | Description |
|---------|-------------|
| **Format** | LeRobot v2.1 (parquet + H264 video) |
| **Episodes** | 100 |
| **Task Variations** | 32 (4 objects × 8 colors) |
| **Camera Views** | 2 (front_cam, workspace_cam) |
| **Resolution** | 640×480 @ 15 FPS |
| **Domain Randomization** | Position, lighting, camera jitter |

### Task Description

The robot performs pick-and-place tasks with natural language instructions:
- "Pick up the red cube and place it in the box"
- "Pick up the blue cylinder and place it in the box"
- "Pick up the green capsule and place it in the box"

## Dataset Structure

```
NOVA/
├── meta/
│   ├── info.json           # Dataset metadata
│   ├── stats.json          # Normalization statistics
│   ├── tasks.jsonl         # Task descriptions
│   └── episodes.jsonl      # Episode information
├── data/
│   └── chunk-000/
│       ├── episode_000000.parquet
│       ├── episode_000001.parquet
│       └── ...
└── videos/
    └── chunk-000/
        ├── observation.images.front_cam/
        │   ├── episode_000000.mp4
        │   └── ...
        └── observation.images.workspace_cam/
            ├── episode_000000.mp4
            └── ...
```

## Data Fields

### State (Proprioception)

| Field | Dimension | Description |
|-------|-----------|-------------|
| `observation.state` | 7 | Joint positions (arm) |

**Joint Names:**
1. `shoulder_pitch` (-180° to 90°)
2. `shoulder_roll` (-180° to 10°)
3. `elbow_yaw` (-90° to 90°)
4. `elbow_pitch` (-125° to 0°)
5. `wrist_roll` (-100° to 100°)
6. `wrist_pitch` (-45° to 45°)
7. `wrist_yaw` (-30° to 30°)

### Action

| Field | Dimension | Description |
|-------|-----------|-------------|
| `action` | 8 | Joint positions (7 arm + 1 gripper) |

**Gripper:** 0 = closed, 1 = open

### Video

| Camera | Resolution | FOV | Format |
|--------|------------|-----|--------|
| `front_cam` | 640×480 | 108° | H264 MP4 |
| `workspace_cam` | 640×480 | 70° | H264 MP4 |

### Language

| Field | Description |
|-------|-------------|
| `annotation.human.task_description` | Natural language task instruction |

## Objects and Colors

### Objects (4 types)
- **Cube** (4cm)
- **Rectangular box**
- **Cylinder**
- **Capsule**

### Colors (8 variations)
- Red, Green, Blue, Yellow
- Cyan, Magenta, Orange, Purple

## Domain Randomization

| Parameter | Range |
|-----------|-------|
| Object position | Workspace-aware random |
| Lighting intensity | 0.5 - 1.0 |
| Camera jitter | ±2° |
| Object type | Random selection |
| Object color | Random selection |

## Usage

### Loading with LeRobot

```python
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("ganatrask/NOVA")

# Access an episode
episode = dataset[0]
print(episode.keys())
# ['observation.state', 'observation.images.front_cam', 'action', ...]
```

### Loading with HuggingFace Datasets

```python
from datasets import load_dataset

dataset = load_dataset("ganatrask/NOVA")
```

### Training GR00T

```bash
python -m gr00t.train \
    --dataset_repo_id ganatrask/NOVA \
    --embodiment_tag reachy2 \
    --video_backend decord \
    --num_gpus 2 \
    --batch_size 64 \
    --max_steps 30000
```

## Collection Details

### Environment

- **Simulator**: MuJoCo via [reachy2_mujoco](https://github.com/pollen-robotics/reachy2_mujoco)
- **Robot**: Reachy 2 humanoid (14-DOF arms, using right arm only)
- **Control Frequency**: 15 Hz

### Collection Process

1. Random object and color selection
2. Random placement within workspace
3. Scripted expert policy execution
4. Recording of observations, states, and actions
5. Automatic episode segmentation

### Collection Command

```bash
python scripts/data_collector.py \
    --episodes 100 \
    --output reachy2_dataset \
    --arm right \
    --randomize-object \
    --randomize-color \
    --cameras front_cam workspace_cam
```

## Statistics

| Statistic | Value |
|-----------|-------|
| Total episodes | 100 |
| Avg. episode length | ~150 steps |
| Collection rate | ~2 episodes/min |
| Total size | ~2 GB |

## Limitations

- **Simulation only**: Data collected in MuJoCo, not real robot
- **Single arm**: Right arm manipulation only
- **Fixed task type**: Pick-and-place only
- **Limited objects**: 4 primitive shapes

## License

This dataset is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/).

## Citation

```bibtex
@misc{nova_dataset_2025,
  title={NOVA Dataset: Reachy 2 Pick-and-Place Demonstrations},
  author={ganatrask},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/ganatrask/NOVA}
}
```

## Acknowledgments

- **[Pollen Robotics](https://www.pollen-robotics.com/)** - Reachy 2 robot and MuJoCo simulation
- **[HuggingFace](https://huggingface.co/)** - LeRobot framework and dataset hosting
- **[DeepMind](https://mujoco.org/)** - MuJoCo physics engine

## Related Resources

- **Model**: [ganatrask/NOVA](https://huggingface.co/ganatrask/NOVA) - Fine-tuned GR00T model
- **Code**: [ganatrask/NOVA](https://github.com/ganatrask/NOVA) - Training and inference code
- **Base Model**: [nvidia/GR00T-N1.6-3B](https://huggingface.co/nvidia/GR00T-N1.6-3B)
- **LeRobot**: [huggingface/lerobot](https://github.com/huggingface/lerobot)