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---
license: bsd-2-clause
pipeline_tag: robotics
---
# Spatial attention recurrent neural network (SARNN)
This repository contains a SARNN (Spatial attention recurrent neural network) model trained with the [MujocoUR5eCable dataset](https://huggingface.co/datasets/RoboManipBaselines/MujocoUR5eCable).
The model is part of **RoboManipBaselines**, a unified framework for imitation learning in robotic manipulation across real and simulation environments.
[[Paper](https://huggingface.co/papers/2509.17057)] [[Project Page](https://isri-aist.github.io/RoboManipBaselines-ProjectPage/)] [[GitHub](https://github.com/isri-aist/RoboManipBaselines)]
## Install
See [GitHub](https://github.com/isri-aist/RoboManipBaselines/blob/master/doc/install.md#SARNN) for installation instructions.
## Policy rollout
To run a trained policy, navigate to the top directory of the `robo_manip_baselines` repository and run:
```console
# Go to the top directory of this repository
$ cd robo_manip_baselines
$ python ./bin/Rollout.py Sarnn MujocoUR5eCable --checkpoint ./checkpoint/Sarnn/<checkpoint_name>/policy_last.ckpt
```
## Technical Details
For more information on the technical details of the SARNN architecture, please see the following paper:
```bibtex
@INPROCEEDINGS{SARNN_ICRA2022,
author = {Ichiwara, Hideyuki and Ito, Hiroshi and Yamamoto, Kenjiro and Mori, Hiroki and Ogata, Tetsuya},
title = {Contact-Rich Manipulation of a Flexible Object based on Deep Predictive Learning using Vision and Tactility},
booktitle = {International Conference on Robotics and Automation},
year = {2022},
pages = {5375-5381},
doi = {10.1109/ICRA46639.2022.9811940}
}
```
## Citation
If you use this framework or model in your work, please cite the RoboManipBaselines 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}
}
```