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Datasets:
ganatrask
/
NOVA

Tasks:
Robotics
Modalities:
Tabular
Video
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
robotics
manipulation
lerobot
humanoid
reachy2
pick-and-place
Libraries:
Datasets
Dask
Polars
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metadata 
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

LeRobot v2.1 100 Episodes Reachy 2

Expert demonstration dataset for training vision-language-action models on Pollen Robotics' Reachy 2 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 

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 

from datasets import load_dataset

dataset = load_dataset("ganatrask/NOVA")

Training GR00T 

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
  • 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 

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.

Citation 

@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

Related Resources