Robot Control Stack (RCS) is a unified and multilayered robot control interface over a MuJoCo simulation and real-world robots. It is designed to be a lean ecosystem for robot learning at scale.

:alt: RCS Architecture
:align: center

• Unified Interface: Seamlessly switch between simulation (MuJoCo) and real hardware.
• Layered Architecture:
  • High-Level: Gymnasium-based Python API for RL and general control.
  • Low-Level: C++ core with Python bindings for performance-critical tasks.
• Extensible: Easy to add new robots and sensors via C++ or Python extensions.
• Lean: Minimal dependencies and overhead.

If you are looking for the most common frame, pose, and scene-setup details first, start here:

• RCS Conventions
• Sim Scene Configuration

:maxdepth: 2
:caption: User Guide

getting_started/index
user_guide/index

:maxdepth: 2
:caption: Apps

apps/index

:maxdepth: 2
:caption: API

api/index

:maxdepth: 2
:caption: Extensions

extensions/index

:maxdepth: 2
:caption: Extending RCS

development/index

:maxdepth: 2
:caption: Project Info

meta/index

If you find RCS useful for your academic work, please consider citing it:

@inproceedings{juelg2026robotcontrolstack,
  title={{Robot Control Stack}: {A} Lean Ecosystem for Robot Learning at Scale}, 
  author={Tobias J{\"u}lg and Pierre Krack and Seongjin Bien and Yannik Blei and Khaled Gamal and Ken Nakahara and Johannes Hechtl and Roberto Calandra and Wolfram Burgard and Florian Walter},
  year={2026},
  booktitle={Proc.~of the IEEE Int.~Conf.~on Robotics \& Automation (ICRA)},
  note={Accepted for publication.}
}

For more scientific info, visit the paper website.