language:
- en
tags:
- robotics
- teleoperation
- humanoid-robot
- motion-capture
- imitation-learning
- mujoco
- bvh
license: apache-2.0
SEW-TWIST G1 Teleoperation Dataset
This dataset contains offline teleoperation trajectories for the Unitree G1 humanoid robot generated using the SEW-MIMIC controller [1] and LaFAN1 BVH motion capture data [2].
The dataset was generated by replaying BVH motion capture sequences through a MuJoCo simulation of the G1 robot and logging the resulting robot state trajectories in a format compatible with TWIST-style imitation learning pipelines [3].
Each trajectory is stored as a .pkl file containing joint states, root pose, and body positions for each simulation frame.
Dataset Structure
dataset/
│
├── *.pkl # Motion trajectories
├── metadata.csv # Optional metadata per sequence
└── README.md
Each .pkl file contains a single trajectory sequence recorded from BVH playback.
Data Format
Each .pkl file contains a Python dictionary with the following structure:
{
"fps": float,
"root_pos": np.ndarray,
"root_rot": np.ndarray,
"dof_pos": np.ndarray,
"local_body_pos": np.ndarray,
"link_body_list": list[str]
}
Fields
fps
float
Frames per second of the recorded trajectory.
root_pos
shape: (T, 3)
dtype: float32
World-space position of the robot root (pelvis mocap frame).
[x, y, z]
Units: meters
root_rot
shape: (T, 4)
dtype: float32
Root orientation quaternion in (x, y, z, w) format.
This is converted from MuJoCo's internal (w, x, y, z) ordering during logging.
dof_pos
shape: (T, 21)
dtype: float32
Joint configuration vector for the robot.
The DOF vector is concatenated as:
[left_leg, right_leg, torso, left_arm, right_arm]
DOF Breakdown
| Body Part | DOF |
|---|---|
| Left Leg | 6 |
| Right Leg | 6 |
| Torso | 3 |
| Left Arm | 4 |
| Right Arm | 4 |
Total: 23 DOF
local_body_pos
shape: (T, N, 3)
dtype: float32
Local body positions for each link relative to the root frame.
Positions are computed as:
local = R_root^T * (x_world - root_pos)
Where
- R_root is the root rotation matrix
- x_world is the world position of the body
link_body_list
list[str] length = N
Names of the robot bodies corresponding to the local_body_pos array.
Example entries include pelvis, hip joints, knees, ankles, torso, shoulders, elbows, wrists, and hands.
Example Usage
import pickle
with open("trajectory.pkl", "rb") as f:
data = pickle.load(f)
print(data.keys())
Output:
dict_keys([
'fps',
'root_pos',
'root_rot',
'dof_pos',
'local_body_pos',
'link_body_list'
])
Intended Use
This dataset can be used for:
- humanoid motion imitation learning
- motion retargeting research
- policy learning from motion capture
- trajectory prediction
- humanoid control benchmarking
Citation
This dataset is released as part of the SEW-MIMIC project
@misc{sew_mimic,
title={A Closed-Form Geometric Retargeting Solver for Upper Body Humanoid Robot Teleoperation},
author={Kong, Chuizheng and Cho, Yunho and Jung, Wonsuhk and others},
year={2026},
note={Project website: https://sew-mimic.com/}
}
Acknowledgements
- LaFAN1 Motion Capture Dataset
- MuJoCo Physics Engine
- SEW Geometric Teleoperation Framework
References
[1] A Closed-Form Geometric Retargeting Solver for Upper Body Humanoid Robot Teleoperation,
Project website: https://sew-mimic.com/
arXiv preprint arXiv:2602.01632, 2026
[2] LaFAN1 Motion Capture Dataset
Ubisoft La Forge.
https://github.com/ubisoft/ubisoft-laforge-animation-dataset
[3] Y. Ze, Z. Chen, J. P. Araújo, Z. Cao, X. B. Peng, J. Wu, and C. K. Liu,
"TWIST: Teleoperated Whole-Body Imitation System,"
Project website: https://yanjieze.com/TWIST/
Data Sources and Licensing
This dataset is generated from the LaFAN1 Motion Capture Dataset provided by Ubisoft La Forge.
The original dataset is licensed under:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
See the original repository for details:
https://github.com/ubisoft/ubisoft-laforge-animation-dataset
Users of this dataset must comply with the license terms of the original dataset.