Datasets:

Modalities:
Video
Size:
< 1K
ArXiv:
Libraries:
Datasets
License:
File size: 1,401 Bytes
2996cb0
 
56a7a26
 
2996cb0
56a7a26
 
 
 
 
 
 
96df284
 
 
dc5ebf1
ebda1d7
ac7a5d6
029dd64
e754784
56a7a26
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
---
license: bsd-2-clause
task_categories:
- robotics
---

# RoboManipBaselines

[**Project Page**](https://isri-aist.github.io/RoboManipBaselines-ProjectPage/) | [**Paper**](https://huggingface.co/papers/2509.17057) | [**GitHub**](https://github.com/isri-aist/RoboManipBaselines)

RoboManipBaselines is a unified framework for imitation learning in robotic manipulation across real and simulation environments. This repository contains expert demonstration datasets used for training and evaluating various imitation learning policies.

## MuJoCo environments
### UR5e
#### MujocoUR5eParticleEnv
Task to scoop up particles.
<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/677b624be4cf361eed593b69/XaWZOCjhmX1nMs_guFb7K.mp4"></video>

The same data can be downloaded [here](https://github.com/isri-aist/RoboManipBaselines/blob/master/doc/dataset_list.md).

## Citation

If you use RoboManipBaselines in your work, please cite the following paper:

```bibtex
@article{RoboManipBaselines_Murooka_2025,
  title={RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments},
  author={Murooka, Masaki and Motoda, Tomohiro and Nakajo, Ryoichi and Oh, Hanbit and Makihara, Koshi and Shirai, Keisuke and Ogata, Tetsuya and Domae, Yukiyasu},
  journal={arXiv preprint arXiv:2509.17057},
  year={2025}
}
```