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Merge doc fix
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Skylark0924 authored Aug 4, 2024
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7 changes: 4 additions & 3 deletions doc/requirements_doc.txt
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scikit-learn
myst-parser
sphinx==6.2.1
sphinx
sphinx_markdown_tables==0.0.17
sphinx_gallery==0.14.0
sphinx-book-theme==1.0.1
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matplotlib==3.7.1
numpy==1.21.6
open3d
kinpy
transformers
astroid<3

lxml
mujoco
mesh_to_sdf
38 changes: 24 additions & 14 deletions doc/source/index.md
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Rofunc package focuses on the **Imitation Learning (IL), Reinforcement Learning (RL) and Learning from Demonstration (
LfD)** for
**(Humanoid) Robot Manipulation**. It provides valuable and convenient python functions, including _demonstration
collection, data
pre-processing, LfD algorithms, planning, and control methods_. We also provide an Isaac Gym-based robot simulator for
collection, data pre-processing, LfD algorithms, planning, and control methods_. We also provide an Isaac Gym-based
robot simulator for
evaluation. This package aims to advance the field by building a full-process toolkit and validation platform that
simplifies and standardizes the process of demonstration data collection, processing, learning, and its deployment on
robots.
Expand Down Expand Up @@ -59,7 +59,7 @@ The available functions and plans can be found as follows.
| | | [`TD3(RofuncRL)`](https://rofunc.readthedocs.io/en/latest/lfd/RofuncRL/TD3.html) | ✅ | | | | | | |
| | | `CQL(RofuncRL)` | ⛔ | | | | | | |
| | | `TD3BC(RofuncRL)` | ⛔ | | | | | | |
| | | [`DTrans(RofuncRL)`](https://rofunc.readthedocs.io/en/latest/lfd/RofuncRL/DTrans.html) | ✅ | | | | | | |
| | | [`DTrans(RofuncRL)`](https://rofunc.readthedocs.io/en/latest/lfd/RofuncRL/DTrans.html) | ✅ | | | | | | |
| | | `EDAC(RofuncRL)` | ⛔ | | | | | | |
| | | [`AMP(RofuncRL)`](https://rofunc.readthedocs.io/en/latest/lfd/RofuncRL/AMP.html) | ✅ | | | | | | |
| | | [`ASE(RofuncRL)`](https://rofunc.readthedocs.io/en/latest/lfd/RofuncRL/ASE.html) | ✅ | | | | | | |
Expand All @@ -70,20 +70,28 @@ The available functions and plans can be found as follows.
If you use rofunc in a scientific publication, we would appreciate citations to the following paper:

```
@software{liu2023rofunc,
title={Rofunc: The full process python package for robot learning from demonstration and robot manipulation},
author={Liu, Junjia and Li, Chenzui and Delehelle, Donatien and Li, Zhihao and Chen, Fei},
month=jun,
year= 2023,
publisher={Zenodo},
doi={10.5281/zenodo.8084510},
url={https://doi.org/10.5281/zenodo.8084510}
@software{liu2023rofunc, 
title = {Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation},
author = {Liu, Junjia and Dong, Zhipeng and Li, Chenzui and Li, Zhihao and Yu, Minghao and Delehelle, Donatien and Chen, Fei},
year = {2023},
publisher = {Zenodo},
doi = {10.5281/zenodo.10016946},
url = {https://doi.org/10.5281/zenodo.10016946},
dimensions = {true},
google_scholar_id = {0EnyYjriUFMC},
}
```

> **Warning** <br>
> **If our code is found to be used in a published paper without proper citation, we reserve the right to address this
> issue formally by contacting the editor to report potential academic misconduct!**
>
> **如果我们的代码被发现用于已发表的论文而没有被恰当引用，我们保留通过正式联系编辑报告潜在学术不端行为的权利。**
## Related Papers

1. Robot cooking with stir-fry: Bimanual non-prehensile manipulation of semi-fluid objects ([IEEE RA-L 2022](https://arxiv.org/abs/2205.05960) | [Code](../../rofunc/learning/RofuncIL/structured_transformer/strans.py))
1. Robot cooking with stir-fry: Bimanual non-prehensile manipulation of semi-fluid
objects ([IEEE RA-L 2022](https://arxiv.org/abs/2205.05960) | [Code](../../rofunc/learning/RofuncIL/structured_transformer/strans.py))

```
@article{liu2022robot,
Expand All @@ -98,7 +106,8 @@ If you use rofunc in a scientific publication, we would appreciate citations to
}
```

2. SoftGPT: Learn Goal-oriented Soft Object Manipulation Skills by Generative Pre-trained Heterogeneous Graph Transformer ([IROS 2023](https://arxiv.org/abs/2306.12677)｜Code coming soon)
2. SoftGPT: Learn Goal-oriented Soft Object Manipulation Skills by Generative Pre-trained Heterogeneous Graph
Transformer ([IROS 2023](https://arxiv.org/abs/2306.12677)｜Code coming soon)

```
@inproceedings{liu2023softgpt,
Expand All @@ -111,7 +120,8 @@ If you use rofunc in a scientific publication, we would appreciate citations to
}
```

3. BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human Demonstration ([IEEE CDC 2023](https://arxiv.org/abs/2307.05933) | [Code](../../rofunc/learning/ml/tpgmm.py))
3. BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human
Demonstration ([IEEE CDC 2023](https://arxiv.org/abs/2307.05933) | [Code](../../rofunc/learning/ml/tpgmm.py))

```
@article{liu2023birp,
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16 changes: 16 additions & 0 deletions doc/source/installation.rst
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# [Option] For MacOS user (brew is required, Isaac Gym based simulator is not supported on MacOS)
sh ./scripts/mac_install.sh
.. tab:: IsaacLab

Please follow the :guilabel:`Isaac Sim` `documentation <https://docs.omniverse.nvidia.com/isaacsim/latest/installation/install_workstation.html>`__ to install the latest Isaac Sim release (:guilabel:`4.1.0`). Make sure the :guilabel:`$HOME/.local/share/ov/pkg/isaac-sim-4.1.0` is the default installation path. Then, run the following command to set up :guilabel:`IsaacLab`.

.. code-block:: shell
git clone https://github.com/Skylark0924/Rofunc.git
cd Rofunc
# Create a conda environment
# Python 3.10 is strongly recommended
conda create -n rofunc python=3.10
.. tab:: OmniIsaacGym

:guilabel:`Isaac Sim` has to be installed firstly by following this `documentation <https://docs.omniverse.nvidia.com/isaacsim/latest/installation/install_workstation.html>`_. Note that the :guilabel:`Isaac Sim` version should be :guilabel:`2022.2.1`, :guilabel:`2023.1.0` is not supported yet since its default python version is `3.10` which is not compatible with :guilabel:`rofunc`.
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