| --- |
| license: bsd-2-clause |
| --- |
| # Spatial attention recurrent neural network (SARNN) |
|
|
| The model was trained with the [MujocoUR5eCable dataset](https://huggingface.co/datasets/RoboManipBaselines/MujocoUR5eCable). |
|
|
| ## Install |
| See [GitHub](https://github.com/isri-aist/RoboManipBaselines/blob/master/doc/install.md#SARNN) for installation. |
|
|
| ## Policy rollout |
| Run a trained policy: |
| ```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, please see the following paper: |
| ```bib |
| @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} |
| } |
| ``` |
|
|
| ## RoboManipBaselines Paper |
| https://huggingface.co/papers/2509.17057 |
|
|
