Search is not available for this dataset
observation.state listlengths 28 28 | observation.contact listlengths 8 8 | action listlengths 28 28 | timestamp float64 0 15.6 | next.reward float64 0 1 | next.done bool 2
classes | task_index int64 0 0 | episode_index int64 0 967 | index int64 0 279k | annotation.human.coarse_action int64 0 0 |
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End of preview. Expand in Data Studio
Unitree G1 Apple Pick and Place with Contact Force Dataset
Front View (Global) |
Side View (Profile) |
Top-Down View (Bird's Eye) |
Ego-Centric View (Robot POV) |
| Multi-view perspectives of the Unitree G1 performing the pick-and-place task. | |
Dataset Description
The Unitree G1 Apple Pick and Place with Contact Force Dataset contains 968 high-quality trajectories with contact force measurements from dexterous hands. The robot picks up a red apple and places it into a bowl using bilateral arms and tri-finger hands. All trajectories include 8-dimensional contact force data from finger and palm sensors.
Key Features:
- 968 successful trajectories with contact force data
- 8D contact force per timestep (bilateral hand sensing)
- 28-DOF control: bilateral arms (7+7) + dexterous hands (7+7)
- 256×256 RGB video at 20 FPS (ego view)
- CuRobo motion planning (collision-free trajectories)
- MuJoCo + RoboCasa simulation with contact dynamics
This dataset extends the base dataset with tactile/contact information for force-aware manipulation research.
Dataset Owner
Junsung Park (@jnsungp)
Seoul National University
night1115@snu.ac.kr
License
Creative Commons Attribution 4.0 International (CC BY 4.0)
Dataset Format
| Modality | Type | Shape | Description |
|---|---|---|---|
| Observation State | float32 |
(28,) |
Joint positions (radians) for arms + hands |
| Observation Contact | float32 |
(8,) |
Contact forces (N) for bilateral hands |
| Action | float32 |
(28,) |
Target joint positions |
| Video | RGB | (256, 256, 3) |
Ego view, 20 FPS, H.264 |
| Language | string |
- | "Pick up the red apple and place it on the bowl" |
Contact Force Configuration (8D)
Contact force magnitudes measured at each finger and palm contact point:
| Index | Contact Point | Description |
|---|---|---|
| 0 | left_thumb |
Left hand thumb tip force |
| 1 | left_index |
Left hand index fingertip force |
| 2 | left_middle |
Left hand middle fingertip force |
| 3 | left_palm |
Left hand palm contact force |
| 4 | right_thumb |
Right hand thumb tip force |
| 5 | right_index |
Right hand index fingertip force |
| 6 | right_middle |
Right hand middle fingertip force |
| 7 | right_palm |
Right hand palm contact force |
Force Measurement:
- Units: Approximate Newtons (N)
- Method: Computed from MuJoCo contact penetration depth
- Formula:
force ≈ max(0, -penetration_depth) × 100.0 - Range: 0 (no contact) to ~50N (strong grasp)
- Use Cases: Grasp quality assessment, force-aware manipulation, slip detection
Joint Configuration (28-DOF)
| Body Part | DOF | Description |
|---|---|---|
| Left Arm | 7 | Shoulder (3) + Elbow (1) + Wrist (3) |
| Right Arm | 7 | Shoulder (3) + Elbow (1) + Wrist (3) |
| Left Hand | 7 | Index (2) + Middle (2) + Thumb (3) |
| Right Hand | 7 | Index (2) + Middle (2) + Thumb (3) |
Dataset Statistics
- Trajectories: 968
- Total Frames: 278,772
- Avg Episode Length:
288 frames (14.4 seconds) - Episode Length Range: 180-400 frames
- Storage Size: ~1.3 GB
- Success Rate: 100%
Download
huggingface-cli download \
--repo-type dataset jnsungp/unitree-g1-robocasa-pick-apple-bowl-contact-1k \
--local-dir ./datasets/g1-contact
Using Python
from datasets import load_dataset
dataset = load_dataset("jnsungp/unitree-g1-robocasa-pick-apple-bowl-contact-1k")
Dataset Structure
dataset_contact_force_1k/
├── data/
│ └── chunk-000/
│ ├── episode_000000.parquet
│ ├── episode_000001.parquet
│ └── ...
├── videos/
│ └── chunk-000/
│ └── observation.images.ego_view/
│ ├── episode_000000.mp4
│ ├── episode_000001.mp4
│ └── ...
├── meta/
│ ├── info.json # Dataset metadata
│ ├── stats.json # Statistics (mean, std, min, max)
│ ├── tasks.jsonl # Task descriptions
│ └── episodes.jsonl # Episode information
└── README.md
Loading Data Example
import pandas as pd
import numpy as np
import cv2
# Load trajectory with contact forces
df = pd.read_parquet("data/chunk-000/episode_000000.parquet")
# Access data
observations = df['observation.state'].values # (N, 28) - joint positions
contact_forces = df['observation.contact'].values # (N, 8) - contact forces
actions = df['action'].values # (N, 28) - target positions
# Analyze contact forces
left_thumb_force = contact_forces[:, 0] # Left thumb contact
right_palm_force = contact_forces[:, 7] # Right palm contact
# Check grasp strength at timestep t
t = 100
total_grasp_force = np.sum(contact_forces[t])
print(f"Total grasp force at t={t}: {total_grasp_force:.2f} N")
# Load video
cap = cv2.VideoCapture("videos/chunk-000/observation.images.ego_view/episode_000000.mp4")
Use Cases
1. Force-Aware Manipulation
Train policies that use contact force feedback for:
- Adaptive grasping (adjust grip based on force)
- Fragile object handling
- Slip detection and prevention
2. Tactile Learning
- Learn force patterns for successful grasps
- Predict object properties from contact forces
- Multi-modal learning (vision + touch)
3. Sim-to-Real Transfer
- Fine-tune models with realistic force profiles
- Domain adaptation with contact dynamics
- Safety-aware manipulation
Technical Details
Simulation:
- Platform: MuJoCo + RoboCasa
- Robot: Unitree G1 (upper body)
- Hands: Dex31 tri-finger hands with contact sensors
- Physics: Realistic contact dynamics and friction
Motion Planning:
- CuRobo (GPU-accelerated)
- Collision-free trajectories
- Smooth cubic interpolation
Contact Sensing:
- Simulated contact forces from MuJoCo
- Per-finger and palm measurements
- Force computed from penetration depth
Comparison with Base Dataset
| Feature | Base Dataset | Contact Force Dataset |
|---|---|---|
| Trajectories | 957 | 968 |
| Joint State | ✓ (28D) | ✓ (28D) |
| Contact Force | ✗ | ✓ (8D) |
| Video | ✓ | ✓ |
| Use Case | Vision-based manipulation | Force-aware manipulation |
Citation
@dataset{park2025unitree_g1_contact,
title={Unitree G1 Apple Pick and Place with Contact Force Dataset},
author={Park, Junsung},
year={2025},
publisher={Hugging Face},
url={https://huggingface.co/datasets/jnsungp/unitree-g1-robocasa-pick-apple-bowl-contact-1k}
}
Acknowledgments
Built with CuRobo, RoboCasa, MuJoCo, and Unitree G1.
Version: 1.0 | Last Updated: November 19, 2025
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