leggedrobotics/rsl_rl
A fast and simple implementation of learning algorithms for robotics.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
2 releases in the last 90 days, the latest 46 days ago, with 39 contributors on GitHub.
Peaked at #81 in the weekly ranking the week of Mar 1, its best in the past year.
Use Cases & Benefits
- Implements fast and simple reinforcement learning algorithms tailored for robotics applications.
- Offers advanced research features like Random Network Distillation and symmetry-based augmentation to enhance exploration and policy symmetry.
- Use for developing and testing PPO-based robotic control policies with integrated curiosity-driven exploration.
- Use for applying student-teacher distillation methods to improve learning efficiency in robotic tasks.
- Use for integrating with simulation environments like NVIDIA Isaac Sim and MuJoCo for realistic robotic learning experiments.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
Other
GitHub could not identify this license; read the LICENSE file before depending on it.
Community files
- README: present
- Contributing guide: present
Watch-outs
- License not identified by GitHub; read the LICENSE file before depending on it.
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From the README
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:
The library currently supports PPO and Student-Teacher Distillation with additional features from our research. These include:
We welcome contributions from the community. Please check our contribution guidelines for more information.
Maintainer: Mayank Mittal and Clemens Schwarke
Affiliation: Robotic Systems Lab, ETH Zurich & NVIDIA
The package can be installed via PyPI with:
or by cloning this repository and installing it with:
The package supports the following logging frameworks which can be configured through
logger:For a demo configuration of PPO, please check the example_config.yaml file.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
Forks
701+55
Open issues
10+3
Compared with peers in Backend
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| anthropics/skills | 187.8K | +2.9K | 15 | — |
| DuarteSantos8/openGym | 19.7K | +2.4K | 60 | 2 days ago |
| shiyu-coder/Kronos | 47.0K | +2.3K | 16 | — |
| NationalSecurityAgency/ghidra | 98.2K | +2.3K | 64 | 14 days ago |
| microsoft/VibeVoice | 56.0K | +1.1K | 29 | — |
| leggedrobotics/rsl_rl | 3.1K | — | 52 | 46 days ago |
| Category median | 56.0K | +2.3K | 29 | — |
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