diff --git a/doc/requirements_doc.txt b/doc/requirements_doc.txt
index 7f4564a21..eefeae081 100644
--- a/doc/requirements_doc.txt
+++ b/doc/requirements_doc.txt
@@ -1,6 +1,6 @@
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
@@ -28,7 +28,8 @@ https://github.com/Skylark0924/Rofunc/releases/download/v0.0.0.9/isaacgym-1.0rc4
matplotlib==3.7.1
numpy==1.21.6
open3d
-kinpy
transformers
astroid<3
-
+lxml
+mujoco
+mesh_to_sdf
diff --git a/doc/source/index.md b/doc/source/index.md
index 9c759c94f..be3f823d2 100644
--- a/doc/source/index.md
+++ b/doc/source/index.md
@@ -16,8 +16,8 @@
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.
@@ -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) | ✅ | | | | | | |
@@ -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**
+> **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,
@@ -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,
@@ -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,
diff --git a/doc/source/installation.rst b/doc/source/installation.rst
index d68c146d4..47db6150d 100644
--- a/doc/source/installation.rst
+++ b/doc/source/installation.rst
@@ -31,6 +31,22 @@ Installation
# [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 `__ 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 `_. 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`.
diff --git a/examples/learning_rl/README.rst b/examples/learning_rl/README.rst
index 8a43a20e7..986d05b7e 100644
--- a/examples/learning_rl/README.rst
+++ b/examples/learning_rl/README.rst
@@ -145,175 +145,186 @@ The following are examples of reinforcement learning methods for robot learning.
'''Inference with pre-trained model in model zoo'''
python examples/learning_rl/IsaacGym_RofuncRL/example_DexterousHands_RofuncRL.py --task=BiShadowHandOver --agent=ppo --inference
- .. list-table:: Task Overview
- :widths: 25 25 25 25
- :header-rows: 1
-
- * - Tasks
- - Animation
- - Performance
- - `ModelZoo `_
- * - `Ant `_
- - .. image:: ../../../img/task_gifs/AntRofuncRLPPO.gif
- -
- - ✅
- * - `Cartpole `_
- -
- -
- -
- * - `FrankaCabinet `_
- - .. image:: ../../../img/task_gifs/FrankaCabinetRofuncRLPPO.gif
- -
- - ✅
- * - `FrankaCubeStack `_
- -
- -
- -
- * - `CURICabinet `_
- - .. image:: ../../../img/task_gifs/CURICabinetRofuncRLPPO.gif
- -
- - ✅
- * - `CURICabinetImage `_
- - .. image:: ../../../img/task_gifs/CURICabinetRofuncRLPPO.gif
- -
- -
- * - `CURICabinetBimanual `_
- -
- -
- -
- * - `CURIQbSoftHandSynergyGrasp `_
- - .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspHammerRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspKnifeRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspLarge_clampRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspMugRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspPhillips_Screw_DriverRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspPower_drillRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspScissorsRofuncRLPPO.gif .. image:: ../../../img/task_gifs/CURIQbSoftHandSynergyGraspSpatulaRofuncRLPPO.gif
- -
- - ✅
- * - `Humanoid `_
- - .. image:: ../../../img/task_gifs/HumanoidRofuncRLPPO.gif
- -
- - ✅
- * - `HumanoidAMP_backflip `_
- - .. image:: ../../../img/task_gifs/HumanoidFlipRofuncRLAMP.gif
- -
- - ✅
- * - `HumanoidAMP_walk `_
- -
- -
- - ✅
- * - `HumanoidAMP_run `_
- - .. image:: ../../../img/task_gifs/HumanoidRunRofuncRLAMP.gif
- -
- - ✅
- * - `HumanoidAMP_dance `_
- - .. image:: ../../../img/task_gifs/HumanoidDanceRofuncRLAMP.gif
- -
- - ✅
- * - `HumanoidAMP_hop `_
- - .. image:: ../../../img/task_gifs/HumanoidHopRofuncRLAMP.gif
- -
- - ✅
- * - `HumanoidASEGetupSwordShield `_
- - .. image:: ../../../img/task_gifs/HumanoidASEGetupSwordShieldRofuncRLASE.gif
- -
- - ✅
- * - `HumanoidASEPerturbSwordShield `_
- - .. image:: ../../../img/task_gifs/HumanoidASEPerturbSwordShieldRofuncRLASE.gif
- -
- - ✅
- * - `HumanoidASEHeadingSwordShield `_
- - .. image:: ../../../img/task_gifs/HumanoidASEHeadingSwordShieldRofuncRLASE.gif
- -
- - ✅
- * - `HumanoidASELocationSwordShield `_
- - .. image:: ../../../img/task_gifs/HumanoidASELocationSwordShieldRofuncRLASE.gif
- -
- - ✅
- * - `HumanoidASEReachSwordShield `_
- -
- -
- - ✅
- * - `HumanoidASEStrikeSwordShield `_
- - .. image:: ../../../img/task_gifs/HumanoidASEStrikeSwordShieldRofuncRLASE.gif
- -
- - ✅
- * - `BiShadowHandBlockStack `_
- - .. image:: ../../../img/task_gifs/BiShadowHandBlockStackRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandBottleCap `_
- - .. image:: ../../../img/task_gifs/BiShadowHandBottleCapRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandCatchAbreast `_
- - .. image:: ../../../img/task_gifs/BiShadowHandCatchAbreastRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandCatchOver2Underarm `_
- - .. image:: ../../../img/task_gifs/BiShadowHandCatchOver2UnderarmRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandCatchUnderarm `_
- - .. image:: ../../../img/task_gifs/BiShadowHandCatchUnderarmRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandDoorOpenInward `_
- - .. image:: ../../../img/task_gifs/BiShadowHandDoorOpenInwardRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandDoorOpenOutward `_
- - .. image:: ../../../img/task_gifs/BiShadowHandDoorOpenOutwardRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandDoorCloseInward `_
- - .. image:: ../../../img/task_gifs/BiShadowHandDoorCloseInwardRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandDoorCloseOutward `_
- - .. image:: ../../../img/task_gifs/BiShadowHandDoorCloseOutwardRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandGraspAndPlace `_
- - .. image:: ../../../img/task_gifs/BiShadowHandGraspAndPlaceRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandLiftUnderarm `_
- - .. image:: ../../../img/task_gifs/BiShadowHandLiftUnderarmRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandOver `_
- - .. image:: ../../../img/task_gifs/BiShadowHandOverRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandPen `_
- - .. image:: ../../../img/task_gifs/BiShadowHandPenRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandPointCloud `_
- -
- -
- -
- * - `BiShadowHandPushBlock `_
- - .. image:: ../../../img/task_gifs/BiShadowHandPushBlockRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandReOrientation `_
- - .. image:: ../../../img/task_gifs/BiShadowHandReOrientationRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandScissors `_
- - .. image:: ../../../img/task_gifs/BiShadowHandScissorsRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandSwingCup `_
- - .. image:: ../../../img/task_gifs/BiShadowHandSwingCupRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandSwitch `_
- - .. image:: ../../../img/task_gifs/BiShadowHandSwitchRofuncRLPPO.gif
- -
- - ✅
- * - `BiShadowHandTwoCatchUnderarm `_
- - .. image:: ../../../img/task_gifs/BiShadowHandTwoCatchUnderarmRofuncRLPPO.gif
- -
- - ✅
+ .. table:: Task Overview
+ :widths: 20 35 35 10
+
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | Tasks | Animation | Performance | |ModelZoo| |
+ +==================+=============================+===============================+=============+
+ | |Ant| | |Ant-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |Cartpole| | | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |FrC| | |FrC-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |FCS| | | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |CUC| | |CUC-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |CCI| | |CCI-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |CCB| | | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |CSG| | |CSG-gif1| | | ✅ |
+ | | |CSG-gif2| | | |
+ | | |CSG-gif3| | | |
+ | | |CSG-gif4| | | |
+ | | |CSG-gif5| | | |
+ | | |CSG-gif6| | | |
+ | | |CSG-gif7| | | |
+ | | |CSG-gif8| | | |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |Hod| | |Hod-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HAB| | |HAB-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HAW| | | | |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HAR| | |HAR-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HAD| | |HAD-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HAH| | |HAH-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HEG| | |HEG-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HEP| | |HEP-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HEH| | |HEH-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HER| | | | |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HEL| | |HEL-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |HES| | |HES-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SBS| | |SBS-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SBC| | |SBC-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SCA| | |SCA-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SU2| | |SU2-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SCU| | |SCU-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SOI| | |SOI-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SOO| | |SOO-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SCI| | |SCI-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SCO| | |SCO-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SGP| | |SGP-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SLU| | |SLU-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SHO| | |SHO-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SPE| | |SPE-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SPC| | | | |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SPB| | |SPB-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SRO| | |SRO-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SSC| | |SSC-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SSW| | |SSW-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |SWH| | |SWH-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+ | |STC| | |STC-gif| | | ✅ |
+ +------------------+-----------------------------+-------------------------------+-------------+
+
+
+
+ .. |Ant-gif| image:: ../../img/task_gifs/AntRofuncRLPPO.gif
+ .. |FrC-gif| image:: ../../img/task_gifs/FrankaCabinetRofuncRLPPO.gif
+ .. |CUC-gif| image:: ../../img/task_gifs/CURICabinetRofuncRLPPO.gif
+ .. |CCI-gif| image:: ../../img/task_gifs/CURICabinetRofuncRLPPO.gif
+ .. |CSG-gif1| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspSpatulaRofuncRLPPO.gif
+ .. |CSG-gif2| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspHammerRofuncRLPPO.gif
+ .. |CSG-gif3| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspKnifeRofuncRLPPO.gif
+ .. |CSG-gif4| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspLarge_clampRofuncRLPPO.gif
+ .. |CSG-gif5| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspMugRofuncRLPPO.gif
+ .. |CSG-gif6| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspPhillips_Screw_DriverRofuncRLPPO.gif
+ .. |CSG-gif7| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspPower_drillRofuncRLPPO.gif
+ .. |CSG-gif8| image:: ../../img/task_gifs/CURIQbSoftHandSynergyGraspScissorsRofuncRLPPO.gif
+ .. |Hod-gif| image:: ../../img/task_gifs/HumanoidRofuncRLPPO.gif
+ .. |HAB-gif| image:: ../../img/task_gifs/HumanoidFlipRofuncRLAMP.gif
+ .. |HAR-gif| image:: ../../img/task_gifs/HumanoidRunRofuncRLAMP.gif
+ .. |HAD-gif| image:: ../../img/task_gifs/HumanoidDanceRofuncRLAMP.gif
+ .. |HAH-gif| image:: ../../img/task_gifs/HumanoidHopRofuncRLAMP.gif
+ .. |HEG-gif| image:: ../../img/task_gifs/HumanoidASEGetupSwordShieldRofuncRLASE.gif
+ .. |HEP-gif| image:: ../../img/task_gifs/HumanoidASEPerturbSwordShieldRofuncRLASE.gif
+ .. |HEH-gif| image:: ../../img/task_gifs/HumanoidASEHeadingSwordShieldRofuncRLASE.gif
+ .. |HEL-gif| image:: ../../img/task_gifs/HumanoidASELocationSwordShieldRofuncRLASE.gif
+ .. |HES-gif| image:: ../../img/task_gifs/HumanoidASEStrikeSwordShieldRofuncRLASE.gif
+ .. |SBS-gif| image:: ../../img/task_gifs/BiShadowHandBlockStackRofuncRLPPO.gif
+ .. |SBC-gif| image:: ../../img/task_gifs/BiShadowHandBottleCapRofuncRLPPO.gif
+ .. |SCA-gif| image:: ../../img/task_gifs/BiShadowHandCatchAbreastRofuncRLPPO.gif
+ .. |SU2-gif| image:: ../../img/task_gifs/BiShadowHandCatchOver2UnderarmRofuncRLPPO.gif
+ .. |SCU-gif| image:: ../../img/task_gifs/BiShadowHandCatchUnderarmRofuncRLPPO.gif
+ .. |SOI-gif| image:: ../../img/task_gifs/BiShadowHandDoorOpenInwardRofuncRLPPO.gif
+ .. |SOO-gif| image:: ../../img/task_gifs/BiShadowHandDoorOpenOutwardRofuncRLPPO.gif
+ .. |SCI-gif| image:: ../../img/task_gifs/BiShadowHandDoorCloseInwardRofuncRLPPO.gif
+ .. |SCO-gif| image:: ../../img/task_gifs/BiShadowHandDoorCloseOutwardRofuncRLPPO.gif
+ .. |SGP-gif| image:: ../../img/task_gifs/BiShadowHandGraspAndPlaceRofuncRLPPO.gif
+ .. |SLU-gif| image:: ../../img/task_gifs/BiShadowHandLiftUnderarmRofuncRLPPO.gif
+ .. |SHO-gif| image:: ../../img/task_gifs/BiShadowHandOverRofuncRLPPO.gif
+ .. |SPE-gif| image:: ../../img/task_gifs/BiShadowHandPenRofuncRLPPO.gif
+ .. |SPB-gif| image:: ../../img/task_gifs/BiShadowHandPushBlockRofuncRLPPO.gif
+ .. |SRO-gif| image:: ../../img/task_gifs/BiShadowHandReOrientationRofuncRLPPO.gif
+ .. |SSC-gif| image:: ../../img/task_gifs/BiShadowHandScissorsRofuncRLPPO.gif
+ .. |SSW-gif| image:: ../../img/task_gifs/BiShadowHandSwingCupRofuncRLPPO.gif
+ .. |SWH-gif| image:: ../../img/task_gifs/BiShadowHandSwitchRofuncRLPPO.gif
+ .. |STC-gif| image:: ../../img/task_gifs/BiShadowHandTwoCatchUnderarmRofuncRLPPO.gif
+
+ .. |ModelZoo| replace:: `Model Zoo `__
+ .. |Ant| replace:: `Ant `__
+ .. |Cartpole| replace:: `Cartpole `__
+ .. |FrC| replace:: `FrankaCabinet `__
+ .. |FCS| replace:: `FrankaCubeStack `__
+ .. |CUC| replace:: `CURICabinet `__
+ .. |CCI| replace:: `CURICabinet Image `__
+ .. |CCB| replace:: `CURICabinet Bimanual `__
+ .. |CSG| replace:: `CURIQbSoftHand SynergyGrasp `__
+ .. |Hod| replace:: `Humanoid `__
+ .. |HAB| replace:: `HumanoidAMP Backflip `__
+ .. |HAW| replace:: `HumanoidAMP Walk `__
+ .. |HAR| replace:: `HumanoidAMP Run `__
+ .. |HAD| replace:: `HumanoidAMP Dance `__
+ .. |HAH| replace:: `HumanoidAMP Hop `__
+ .. |HEG| replace:: `HumanoidASE GetupSwordShield `__
+ .. |HEP| replace:: `HumanoidASE PerturbSwordShield `__
+ .. |HEH| replace:: `HumanoidASE HeadingSwordShield `__
+ .. |HER| replace:: `HumanoidASE ReachSwordShield `__
+ .. |HEL| replace:: `HumanoidASE LocationSwordShield `__
+ .. |HES| replace:: `HumanoidASE StrikeSwordShield `__
+ .. |SBS| replace:: `BiShadowHand BlockStack `__
+ .. |SBC| replace:: `BiShadowHand BottleCap `__
+ .. |SCA| replace:: `BiShadowHand CatchAbreast `__
+ .. |SU2| replace:: `BiShadowHand CatchOver2Underarm `__
+ .. |SCU| replace:: `BiShadowHand CatchUnderarm `__
+ .. |SOI| replace:: `BiShadowHand DoorOpenInward `__
+ .. |SOO| replace:: `BiShadowHand DoorOpenOutward `__
+ .. |SCI| replace:: `BiShadowHand DoorCloseInward `__
+ .. |SCO| replace:: `BiShadowHand DoorCloseOutward `__
+ .. |SGP| replace:: `BiShadowHand GraspAndPlace `__
+ .. |SLU| replace:: `BiShadowHand LiftUnderarm `__
+ .. |SHO| replace:: `BiShadowHand Over `__
+ .. |SPE| replace:: `BiShadowHand Pen `__
+ .. |SPC| replace:: `BiShadowHand PointCloud `__
+ .. |SPB| replace:: `BiShadowHand PushBlock `__
+ .. |SRO| replace:: `BiShadowHand ReOrientation `__
+ .. |SSC| replace:: `BiShadowHand Scissors `__
+ .. |SSW| replace:: `BiShadowHand SwingCup `__
+ .. |SWH| replace:: `BiShadowHand Switch `__
+ .. |STC| replace:: `BiShadowHand TwoCatchUnderarm `__
.. tab:: OmniIsaacGym
diff --git a/rofunc/utils/robolab/coord/transform_tensor.py b/rofunc/utils/robolab/coord/transform_tensor.py
new file mode 100644
index 000000000..a7bef0202
--- /dev/null
+++ b/rofunc/utils/robolab/coord/transform_tensor.py
@@ -0,0 +1,463 @@
+# Copyright 2023, Junjia LIU, jjliu@mae.cuhk.edu.hk
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Coordinate transformation functions with tensor support
+----------------------------------------------------------
+| This module provides functions to convert between different coordinate systems with tensor support.
+| Note
+
+1. Quaternions ix+jy+kz+w are represented as [x, y, z, w].
+2. Euler angles are represented as [roll, pitch, yaw], in radians. The rotation order is ZYX.
+3. Rotation matrices are represented as (3, 3).
+4. Homogeneous matrices are represented as (4, 4).
+"""
+
+import numpy as np
+import torch
+
+# epsilon for testing whether a number is close to zero
+_EPS = torch.finfo(torch.float32).eps * 4.0
+
+
+def check_pos_tensor(pos):
+ """
+ Check if the input position is valid.
+
+ :param pos: (batch, 3) or (3, )
+ :return: position
+
+ >>> check_pos_tensor([0, 0, 0])
+ tensor([[0., 0., 0.]])
+ >>> check_pos_tensor([[0, 0, 0]])
+ tensor([[0., 0., 0.]])
+ >>> check_pos_tensor(np.array([0, 0, 0]))
+ tensor([[0., 0., 0.]])
+ """
+ pos = torch.tensor(pos, dtype=torch.float32)
+ if len(pos.shape) == 1:
+ pos = pos.unsqueeze(0)
+ assert pos.shape[-1] == 3, "The last dimension of the input tensor should be 3."
+ return pos
+
+
+def check_quat_tensor(quat):
+ """
+ Check if the input quat is normalized.
+
+ :param quat: (batch, 4) or (4, )
+ :return: normalized quat
+
+ >>> check_quat_tensor([0, 5, 0, 1])
+ tensor([[0.0000, 0.9806, 0.0000, 0.1961]])
+ >>> check_quat_tensor([[0, 2, 0, 1]])
+ tensor([[0.0000, 0.8944, 0.0000, 0.4472]])
+ >>> check_quat_tensor(np.array([1, 5, 5.435, 1]))
+ tensor([[0.1330, 0.6650, 0.7228, 0.1330]])
+ """
+ quat = torch.tensor(quat, dtype=torch.float32)
+ if len(quat.shape) == 1:
+ quat = quat.unsqueeze(0)
+ assert quat.shape[-1] == 4, "The last dimension of the input tensor should be 4."
+ norm = torch.norm(quat, dim=-1, keepdim=True)
+ if torch.any(norm == 0):
+ raise ValueError(
+ f"The input quat is invalid. The index of the invalid quat is {torch.where(norm == 0)[0]}")
+ quat = quat / (norm + _EPS)
+ return quat
+
+
+def check_rot_matrix_tensor(rot_matrix):
+ """
+ Check if the input rotation matrix is valid, orthogonal, and normalize it if necessary.
+
+ :param rot_matrix: Input rotation matrix
+ :return: Validated and normalized rotation matrix
+
+ >>> from rofunc.utils.robolab.coord.transform import random_rot_matrix
+ >>> rot_matrix = random_rot_matrix() * 3
+ >>> torch.allclose(check_rot_matrix_tensor(rot_matrix) * 3, torch.tensor(rot_matrix, dtype=torch.float32))
+ True
+ """
+ rot_matrix = torch.tensor(rot_matrix, dtype=torch.float32)
+ if len(rot_matrix.shape) == 2:
+ rot_matrix = rot_matrix.unsqueeze(0)
+ # Check if the matrix is square
+ if rot_matrix.shape[-1] != rot_matrix.shape[-2]:
+ raise ValueError("Input matrix is not square.")
+
+ # # Check orthogonality: R^T * R should be equal to the identity matrix
+ # identity_matrix = torch.eye(rot_matrix.shape[-1])
+ # matrix_product = torch.matmul(rot_matrix.transpose(-1, -2), rot_matrix)
+ # if not torch.allclose(matrix_product, identity_matrix):
+ # raise ValueError("Input matrix is not orthogonal.")
+
+ # Normalize the matrix if necessary
+ normalized_rot_matrix = rot_matrix
+ column_norms = torch.norm(normalized_rot_matrix, dim=-2)
+ if not torch.allclose(column_norms, torch.ones_like(column_norms)):
+ normalized_rot_matrix = normalized_rot_matrix / column_norms.unsqueeze(-1)
+
+ return normalized_rot_matrix
+
+
+def check_euler_tensor(euler):
+ """
+ Check if the input euler angles are valid.
+
+ :param euler: (batch, 3) or (3, )
+ :return: euler angles
+
+ >>> check_euler_tensor([1.57, 0, 0])
+ tensor([[1.5700, 0.0000, 0.0000]])
+ >>> check_euler_tensor([[0, 0, 0]])
+ tensor([[0., 0., 0.]])
+ >>> check_euler_tensor(np.array([0, 0, 0]))
+ tensor([[0., 0., 0.]])
+ """
+ euler = torch.tensor(euler, dtype=torch.float32)
+ if len(euler.shape) == 1:
+ euler = euler.unsqueeze(0)
+ assert euler.shape[-1] == 3, "The last dimension of the input tensor should be 3."
+ return euler
+
+
+def random_quat_tensor(batch_size, rand=None):
+ """
+ Return uniform random unit quat.
+
+ :param batch_size: Batch size
+ :param rand: Random number generator (optional)
+ :return: Random unit quat, [x, y, z, w]
+
+ >>> torch.allclose(torch.norm(random_quat_tensor(100), dim=-1), torch.ones(100))
+ True
+ >>> rand_quat = random_quat_tensor(100)
+ >>> torch.allclose(check_quat_tensor(rand_quat), rand_quat)
+ True
+ """
+ if rand is None:
+ rand = torch.rand
+
+ random_values = rand(batch_size, 3)
+ r1 = torch.sqrt(1 - random_values[:, 0])
+ r2 = torch.sqrt(random_values[:, 0])
+ pi2 = 2 * torch.pi
+ t1 = pi2 * random_values[:, 1]
+ t2 = pi2 * random_values[:, 2]
+
+ x = r1 * torch.sin(t1)
+ y = r1 * torch.cos(t1)
+ z = r2 * torch.sin(t2)
+ w = r2 * torch.cos(t2)
+
+ quat = torch.stack([x, y, z, w], dim=-1)
+
+ return quat
+
+
+def random_rot_matrix_tensor(batch_size, rand=None):
+ """
+ Generate random rotation matrix. quat = [x, y, z, w].
+
+ :param batch_size: Batch size
+ :param rand: Random number generator (optional)
+ :return: Random rotation matrix
+
+ >>> rand_rot_matrix = random_rot_matrix_tensor(100)
+ >>> torch.allclose(rand_rot_matrix.det(), torch.ones(100))
+ True
+ >>> torch.allclose(check_rot_matrix_tensor(rand_rot_matrix), rand_rot_matrix)
+ True
+ >>> from rofunc.utils.robolab.coord.transform import check_rot_matrix
+ >>> torch.allclose(torch.tensor(check_rot_matrix(rand_rot_matrix[0]), dtype=torch.float32), rand_rot_matrix[0])
+ True
+ """
+ if rand is None:
+ rand = torch.rand
+
+ quat = random_quat_tensor(batch_size, rand)
+
+ wx, wy, wz, ww = quat[:, 0], quat[:, 1], quat[:, 2], quat[:, 3]
+ xx = wx * wx
+ xy = wx * wy
+ xz = wx * wz
+ xw = wx * ww
+ yy = wy * wy
+ yz = wy * wz
+ yw = wy * ww
+ zz = wz * wz
+ zw = wz * ww
+
+ rot_matrix = torch.stack(
+ [
+ 1 - 2 * (yy + zz),
+ 2 * (xy - zw),
+ 2 * (xz + yw),
+ 2 * (xy + zw),
+ 1 - 2 * (xx + zz),
+ 2 * (yz - xw),
+ 2 * (xz - yw),
+ 2 * (yz + xw),
+ 1 - 2 * (xx + yy),
+ ],
+ dim=1,
+ ).view(batch_size, 3, 3)
+
+ return rot_matrix
+
+
+def quat_from_rot_matrix_tensor(rot_matrix):
+ """
+ Convert rotation matrix to quat. [x, y, z, w]
+
+ :param rot_matrix:
+ :return: quat, [x, y, z, w]
+
+ >>> quat_from_rot_matrix_tensor([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+ tensor([[0., 0., 0., 1.]])
+ >>> quat_from_rot_matrix_tensor([[0.9362934, -0.2896295, 0.1986693], [0.3129918, 0.9447025, -0.0978434], [-0.1593451, 0.1537920, 0.9751703]])
+ tensor([[0.0641, 0.0912, 0.1534, 0.9819]])
+ >>> rand_rot_matrix = random_rot_matrix_tensor(100)
+ >>> torch.allclose(check_rot_matrix_tensor(rand_rot_matrix), rot_matrix_from_quat_tensor(quat_from_rot_matrix_tensor(rand_rot_matrix)), rtol=1e-03, atol=1e-03)
+ True
+ """
+ rot_matrix = check_rot_matrix_tensor(rot_matrix)
+
+ trace = rot_matrix[:, 0, 0] + rot_matrix[:, 1, 1] + rot_matrix[:, 2, 2]
+ r = torch.sqrt(1 + trace)
+
+ qw = 0.5 * r
+ qx = (rot_matrix[:, 2, 1] - rot_matrix[:, 1, 2]) / (2 * r)
+ qy = (rot_matrix[:, 0, 2] - rot_matrix[:, 2, 0]) / (2 * r)
+ qz = (rot_matrix[:, 1, 0] - rot_matrix[:, 0, 1]) / (2 * r)
+
+ quat = torch.stack([qx, qy, qz, qw], dim=-1)
+ return quat
+
+
+def quat_from_euler_tensor(euler):
+ """
+ Convert euler angles to quat. The rotation order is ZYX.
+
+ :param euler: (batch, 3) or (3, ), [roll, pitch, yaw], the rotation order is ZYX.
+ :return: quat, [x, y, z, w]
+
+ >>> quat_from_euler_tensor([0, 0, 0])
+ tensor([[0., 0., 0., 1.]])
+ >>> quat_from_euler_tensor([[0, 0, 0]])
+ tensor([[0., 0., 0., 1.]])
+ >>> quat_from_euler_tensor(np.array([0, 0, 0]))
+ tensor([[0., 0., 0., 1.]])
+ >>> quat_from_euler_tensor([[0, 1.23, 0.57], [0.5, 0.3, 0.7], [0.1, 0.2, 0.3]])
+ tensor([[-0.1622, 0.5537, 0.2296, 0.7838],
+ [ 0.1801, 0.2199, 0.2938, 0.9126],
+ [ 0.0343, 0.1060, 0.1436, 0.9833]])
+ """
+ euler = check_euler_tensor(euler)
+
+ roll = euler[:, 0]
+ pitch = euler[:, 1]
+ yaw = euler[:, 2]
+
+ cy = torch.cos(yaw * 0.5)
+ sy = torch.sin(yaw * 0.5)
+ cp = torch.cos(pitch * 0.5)
+ sp = torch.sin(pitch * 0.5)
+ cr = torch.cos(roll * 0.5)
+ sr = torch.sin(roll * 0.5)
+
+ qx = sr * cp * cy - cr * sp * sy
+ qy = cr * sp * cy + sr * cp * sy
+ qz = cr * cp * sy - sr * sp * cy
+ qw = cr * cp * cy + sr * sp * sy
+
+ quat = torch.stack([qx, qy, qz, qw], dim=-1)
+
+ return quat
+
+
+def rot_matrix_from_quat_tensor(quat):
+ """
+ Convert quat to rotation matrix.
+
+ :param quat: [x, y, z, w]
+ :return:
+
+ >>> rot_matrix_from_quat_tensor([0, 0, 0, 1])
+ tensor([[[1., 0., 0.],
+ [0., 1., 0.],
+ [0., 0., 1.]]])
+ >>> rot_matrix_from_quat_tensor([[0.06146124, 0, 0, 0.99810947], [0.2794439, 0.0521324, 0.3632374, 0.8872722]])
+ tensor([[[ 1.0000, 0.0000, 0.0000],
+ [ 0.0000, 0.9924, -0.1227],
+ [ 0.0000, 0.1227, 0.9924]],
+
+ [[ 0.7307, -0.6154, 0.2955],
+ [ 0.6737, 0.5799, -0.4580],
+ [ 0.1105, 0.5338, 0.8384]]])
+ """
+ quat = check_quat_tensor(quat)
+ x, y, z, w = quat[:, 0], quat[:, 1], quat[:, 2], quat[:, 3]
+
+ r11 = 1 - 2 * (y ** 2 + z ** 2)
+ r12 = 2 * (x * y - z * w)
+ r13 = 2 * (x * z + y * w)
+ r21 = 2 * (x * y + z * w)
+ r22 = 1 - 2 * (x ** 2 + z ** 2)
+ r23 = 2 * (y * z - x * w)
+ r31 = 2 * (x * z - y * w)
+ r32 = 2 * (y * z + x * w)
+ r33 = 1 - 2 * (x ** 2 + y ** 2)
+
+ rot_matrix = torch.stack([
+ torch.stack([r11, r12, r13], dim=-1),
+ torch.stack([r21, r22, r23], dim=-1),
+ torch.stack([r31, r32, r33], dim=-1)
+ ], dim=-2)
+
+ return check_rot_matrix_tensor(rot_matrix)
+
+
+def rot_matrix_from_euler_tensor(euler):
+ """
+ Convert euler angles to rotation matrix.
+
+ :param euler: (batch, 3) or (3, ), [roll, pitch, yaw] in radian
+ :return: Rotation matrix
+
+ >>> rot_matrix_from_euler_tensor([0, 0, 0])
+ tensor([[[1., 0., 0.],
+ [0., 1., 0.],
+ [-0., 0., 1.]]])
+ >>> rot_matrix_from_euler_tensor([[0.5, 0.3, 0.7], [1.33, 0.2, -0.03]])
+ tensor([[[ 0.7307, -0.4570, 0.5072],
+ [ 0.6154, 0.7625, -0.1996],
+ [-0.2955, 0.4580, 0.8384]],
+
+ [[ 0.9796, 0.2000, 0.0182],
+ [-0.0294, 0.2326, -0.9721],
+ [-0.1987, 0.9518, 0.2337]]])
+ """
+ euler = check_euler_tensor(euler)
+
+ roll = euler[:, 0]
+ pitch = euler[:, 1]
+ yaw = euler[:, 2]
+
+ cos_r = torch.cos(roll)
+ sin_r = torch.sin(roll)
+ cos_p = torch.cos(pitch)
+ sin_p = torch.sin(pitch)
+ cos_y = torch.cos(yaw)
+ sin_y = torch.sin(yaw)
+
+ batch_size = euler.size(0)
+ device = euler.device
+
+ rot_matrix = torch.zeros((batch_size, 3, 3), device=device)
+ rot_matrix[:, 0, 0] = cos_y * cos_p
+ rot_matrix[:, 0, 1] = cos_y * sin_p * sin_r - sin_y * cos_r
+ rot_matrix[:, 0, 2] = cos_y * sin_p * cos_r + sin_y * sin_r
+ rot_matrix[:, 1, 0] = sin_y * cos_p
+ rot_matrix[:, 1, 1] = sin_y * sin_p * sin_r + cos_y * cos_r
+ rot_matrix[:, 1, 2] = sin_y * sin_p * cos_r - cos_y * sin_r
+ rot_matrix[:, 2, 0] = -sin_p
+ rot_matrix[:, 2, 1] = cos_p * sin_r
+ rot_matrix[:, 2, 2] = cos_p * cos_r
+
+ return rot_matrix
+
+
+def euler_from_quat_tensor(quat):
+ """
+ Convert quat to euler angles.
+
+ :param quat: [x, y, z, w]
+ :return: euler angles, [roll, pitch, yaw] in radian
+
+ >>> euler_from_quat_tensor(torch.tensor([[0, 0, 0, 1.]]))
+ tensor([[0., 0., 0.]])
+ >>> euler_from_quat_tensor(torch.tensor([[0.06146124, 0, 0, 0.99810947], [0.2794439, 0.0521324, 0.3632374, 0.8872722]]))
+ tensor([[ 0.1230, 0.0000, 0.0000],
+ [ 0.5669, -0.1107, 0.7449]])
+ """
+ quat = check_quat_tensor(quat)
+
+ qx = quat[:, 0]
+ qy = quat[:, 1]
+ qz = quat[:, 2]
+ qw = quat[:, 3]
+
+ roll = torch.atan2(2 * (qw * qx + qy * qz), 1 - 2 * (qx * qx + qy * qy))
+ pitch = torch.asin(torch.clamp(2 * (qw * qy - qz * qx), -1, 1))
+ yaw = torch.atan2(2 * (qw * qz + qx * qy), 1 - 2 * (qy * qy + qz * qz))
+
+ euler = torch.stack([roll, pitch, yaw], dim=-1)
+
+ return euler
+
+
+def euler_from_rot_matrix_tensor(rot_matrix):
+ """
+ Convert rotation matrix to euler angles.
+
+ :param rot_matrix:
+ :return:
+
+ >>> euler_from_rot_matrix_tensor([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+ tensor([[0., -0., 0.]])
+ >>> euler_from_rot_matrix_tensor([[[ 0.7307, -0.4570, 0.5072], [ 0.6154, 0.7625, -0.1996], [-0.2955, 0.4580, 0.8384]], [[ 0.9796, 0.2000, 0.0182], [-0.0294, 0.2326, -0.9721], [-0.1987, 0.9518, 0.2337]]])
+ tensor([[ 0.5000, 0.3000, 0.6999],
+ [ 1.3300, 0.2000, -0.0300]])
+ """
+ rot_matrix = check_rot_matrix_tensor(rot_matrix)
+
+ r11, r12, r13 = rot_matrix[:, 0, 0], rot_matrix[:, 0, 1], rot_matrix[:, 0, 2]
+ r21, r22, r23 = rot_matrix[:, 1, 0], rot_matrix[:, 1, 1], rot_matrix[:, 1, 2]
+ r31, r32, r33 = rot_matrix[:, 2, 0], rot_matrix[:, 2, 1], rot_matrix[:, 2, 2]
+
+ pitch = -torch.asin(r31)
+ roll = torch.atan2(r32 / torch.cos(pitch), r33 / torch.cos(pitch))
+ yaw = torch.atan2(r21 / torch.cos(pitch), r11 / torch.cos(pitch))
+
+ euler = torch.stack([roll, pitch, yaw], dim=-1)
+
+ return euler
+
+
+def homo_matrix_from_quat_tensor(quat, pos=None):
+ """
+ Convert quat and pos to homogeneous matrix
+
+ :param quat:
+ :param pos:
+ :return:
+ """
+ quat = check_quat_tensor(quat)
+ if pos is not None:
+ pos = check_pos_tensor(pos)
+ assert quat.shape[0] == pos.shape[0]
+ else:
+ pos = torch.zeros((quat.shape[0], 3))
+
+ batch_size = quat.shape[0]
+ device = quat.device
+
+ homo_matrix = torch.zeros((batch_size, 4, 4), device=device)
+ rot_matrix = rot_matrix_from_quat_tensor(quat)
+ homo_matrix[:, :3, :3] = rot_matrix
+ homo_matrix[:, :3, 3] = pos
+ homo_matrix[:, 3, 3] = 1
+ return homo_matrix
diff --git a/scripts/mac_install.sh b/scripts/install_mac.sh
similarity index 100%
rename from scripts/mac_install.sh
rename to scripts/install_mac.sh
diff --git a/scripts/install.sh b/scripts/install_w_isaacgym.sh
similarity index 100%
rename from scripts/install.sh
rename to scripts/install_w_isaacgym.sh
diff --git a/scripts/install_w_baselines.sh b/scripts/install_w_isaacgym_w_baselines.sh
similarity index 100%
rename from scripts/install_w_baselines.sh
rename to scripts/install_w_isaacgym_w_baselines.sh
diff --git a/scripts/install_w_isaaclab.sh b/scripts/install_w_isaaclab.sh
new file mode 100644
index 000000000..ed411c08b
--- /dev/null
+++ b/scripts/install_w_isaaclab.sh
@@ -0,0 +1,17 @@
+# Define aliases for the conda environment
+alias pip3rfl="$HOME/anaconda3/envs/rofunc_isaaclab/bin/pip"
+alias py3rfl="$HOME/anaconda3/envs/rofunc_isaaclab/bin/python3.10"
+
+# Download IsaacLab and install it
+cd ../
+git clone https://github.com/isaac-sim/IsaacLab.git
+cd IsaacLab
+ln -s $HOME/.local/share/ov/pkg/isaac-sim-4.1.0 _isaac_sim
+./isaaclab.sh --install
+
+# Install the requirements and rofunc
+pip3rfl install shutup
+pip3rfl install omegaconf
+pip3rfl install hydra-core
+pip3rfl install nestle
+pip3rfl install gdown
\ No newline at end of file
diff --git a/scripts/update.sh b/scripts/update_package.sh
similarity index 100%
rename from scripts/update.sh
rename to scripts/update_package.sh