init commit.

2026-03-23 03:17:59 +08:00
commit fce9166e87
99 changed files with 13778 additions and 0 deletions
--- a/source/rsl_rl/README.md
+++ b/source/rsl_rl/README.md
@@ -0,0 +1,109 @@
+# RSL-RL
+
+A fast and simple implementation of learning algorithms for robotics. For an overview of the library please have a look at https://arxiv.org/pdf/2509.10771.
+
+Environment repositories using the framework:
+
+* **`Isaac Lab`** (built on top of NVIDIA Isaac Sim): https://github.com/isaac-sim/IsaacLab
+* **`Legged Gym`** (built on top of NVIDIA Isaac Gym): https://leggedrobotics.github.io/legged_gym/
+* **`MuJoCo Playground`** (built on top of MuJoCo MJX and Warp): https://github.com/google-deepmind/mujoco_playground/
+* **`mjlab`** (built on top of MuJoCo Warp): https://github.com/mujocolab/mjlab
+
+The library currently supports **PPO** and **Student-Teacher Distillation** with additional features from our research. These include:
+
+* [Random Network Distillation (RND)](https://proceedings.mlr.press/v229/schwarke23a.html) - Encourages exploration by adding
+  a curiosity driven intrinsic reward.
+* [Symmetry-based Augmentation](https://arxiv.org/abs/2403.04359) - Makes the learned behaviors more symmetrical.
+
+We welcome contributions from the community. Please check our contribution guidelines for more
+information.
+
+**Maintainer**: Mayank Mittal and Clemens Schwarke <br/>
+**Affiliation**: Robotic Systems Lab, ETH Zurich & NVIDIA <br/>
+**Contact**: cschwarke@ethz.ch
+
+
+## Setup
+
+The package can be installed via PyPI with:
+
+```bash
+pip install rsl-rl-lib
+```
+
+or by cloning this repository and installing it with:
+
+```bash
+git clone https://github.com/leggedrobotics/rsl_rl
+cd rsl_rl
+pip install -e .
+```
+
+The package supports the following logging frameworks which can be configured through `logger`:
+
+* Tensorboard: https://www.tensorflow.org/tensorboard/
+* Weights & Biases: https://wandb.ai/site
+* Neptune: https://docs.neptune.ai/
+
+For a demo configuration of PPO, please check the [example_config.yaml](config/example_config.yaml) file.
+
+
+## Contribution Guidelines
+
+For documentation, we adopt the [Google Style Guide](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html) for docstrings. Please make sure that your code is well-documented and follows the guidelines.
+
+We use the following tools for maintaining code quality:
+
+- [pre-commit](https://pre-commit.com/): Runs a list of formatters and linters over the codebase.
+- [ruff](https://github.com/astral-sh/ruff): An extremely fast Python linter and code formatter, written in Rust.
+
+Please check [here](https://pre-commit.com/#install) for instructions to set these up. To run over the entire repository, please execute the following command in the terminal:
+
+```bash
+# for installation (only once)
+pre-commit install
+# for running
+pre-commit run --all-files
+```
+
+## Citing
+
+If you use this library for your research, please cite the following work:
+
+```text
+@article{schwarke2025rslrl,
+  title={RSL-RL: A Learning Library for Robotics Research},
+  author={Schwarke, Clemens and Mittal, Mayank and Rudin, Nikita and Hoeller, David and Hutter, Marco},
+  journal={arXiv preprint arXiv:2509.10771},
+  year={2025}
+}
+```
+
+If you use the library with curiosity-driven exploration (random network distillation), please cite:
+
+```text
+@InProceedings{schwarke2023curiosity,
+  title = 	 {Curiosity-Driven Learning of Joint Locomotion and Manipulation Tasks},
+  author =       {Schwarke, Clemens and Klemm, Victor and Boon, Matthijs van der and Bjelonic, Marko and Hutter, Marco},
+  booktitle = 	 {Proceedings of The 7th Conference on Robot Learning},
+  pages = 	 {2594--2610},
+  year = 	 {2023},
+  volume = 	 {229},
+  series = 	 {Proceedings of Machine Learning Research},
+  publisher =    {PMLR},
+  url = 	 {https://proceedings.mlr.press/v229/schwarke23a.html},
+}
+```
+
+If you use the library with symmetry augmentation, please cite:
+
+```text
+@InProceedings{mittal2024symmetry,
+  author={Mittal, Mayank and Rudin, Nikita and Klemm, Victor and Allshire, Arthur and Hutter, Marco},
+  booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)},
+  title={Symmetry Considerations for Learning Task Symmetric Robot Policies},
+  year={2024},
+  pages={7433-7439},
+  doi={10.1109/ICRA57147.2024.10611493}
+}
+```