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---
pretty_name: Retargeted Robot Motion Dataset
license: other
tags:
- robotics
- motion-capture
- robot-motion
- imitation-learning
- reinforcement-learning
dataset_info:
features:
- name: joints_list
dtype: string
- name: joint_positions
dtype: float32
- name: root_position
dtype: float32
- name: root_quaternion
dtype: float32
- name: fps
dtype: float32
- name: duration
dtype: float32
- name: r_forearm
dtype: float32
- name: l_forearm
dtype: float32
- name: r_sole
dtype: float32
- name: l_sole
dtype: float32
splits:
- name: train
num_bytes: null
num_examples: null
download_size: null
dataset_size: null
size_categories:
- 100K<n<1M
---
# Retargeted Robot Motion Dataset
This dataset provides retargeted motion capture sequences for a variety of robotic platforms. The motion data is derived from the [CMU Motion Capture Database](https://mocap.cs.cmu.edu/) and includes a wide range of motion types beyond locomotion — such as gestures, interactions, and full-body activities.
The data has been adapted to match the kinematic structure of specific robots, enabling its use in tasks such as:
- Imitation learning
- Reinforcement learning
- Motion analysis
- Skill learning from demonstration
---
## 📁 Dataset Format
Each `.npy` file contains a dictionary with the following keys:
- `joints_list`: list of joint names
- `joint_positions`: per-frame joint angle vectors
- `root_position`: per-frame 3D position of the robot’s base
- `root_quaternion`: per-frame orientation as quaternions (`xyzw`)
- `fps`: sampling rate of the motion (frames per second)
- `duration`: total sequence duration in seconds
- `r_forearm`, `l_forearm`: optional 3D positions of the forearms
- `r_sole`, `l_sole`: optional 3D positions of the soles of the feet
> All lists should have consistent lengths across time frames.
### Example
```python
{
"joints_list": ["joint_1", "joint_2", ...],
"joint_positions": [np.array([...]), ...],
"root_position": [np.array([x, y, z]), ...],
"root_quaternion": [np.array([x, y, z, w]), ...],
"fps": 120.0,
"duration": 3.2
}
```
---
## 📂 Repository Structure
The dataset repository is organized by robot model:
```
.
├── ergocub/
│ ├── wave_hand.npy
│ ├── walk_forward.npy
│ └── ...
├── another_robot/
│ └── ...
├── README.md
```
Each folder contains `.npy` files with motion data retargeted to that specific robot's model.
---
## 📄 License
Original motion capture data © Carnegie Mellon University.
Retargeted datasets are provided for research purposes under the BSD 3-Clause license. |