# mc-mujoco: Simulating Articulated Robots with FSM Controllers in MuJoCo

arXiv: https://arxiv.org/abs/2209.00274 · HTML: https://mlsanity.com/paper/2209.00274/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2022.

## Built on by (most cited first, 5 of 5)

- [Learning Bipedal Walking for Humanoids with Current Feedback](https://mlsanity.com/paper/2303.03724/) (2023)
- [Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning](https://mlsanity.com/paper/2504.13619/) (2025)
- [Safe Execution of RL Policies Via Acceleration-Based CBF-QP Constraint Enforcement for Real-World Robotic Deployments](https://mlsanity.com/paper/2607.14488/) (2026)
- [HuMam: Humanoid Motion Control via End-to-End Deep Reinforcement Learning with Mamba](https://mlsanity.com/paper/2509.18046/) (2025)
- [Towards An LLM-Driven Unified Conversion Framework for BT and FSM in Autonomous Intelligent Systems](https://mlsanity.com/paper/2609.29228/) (2026)

## Abstract (arXiv)

For safe and reliable deployment of any robot controller on the real hardware platform, it is generally a necessary practice to comprehensively assess the performance of the controller with the specific robot in a realistic simulation environment beforehand. While there exist several software solutions that can provide the core physics engine for this purpose, it is often a cumbersome and error-prone effort to interface the simulation environment with the robot controller being evaluated. The controller may have a complex structure consisting of multiple states and transitions within a finite-state machine (FSM), and may even require input through a GUI. In this work, we present mc-mujoco -- an open-source software framework that forms an interface between the MuJoCo physics simulator and the mc-rtc robot control framework. We provide implementation details and describe the process for adding support for essentially any new robot. We also demonstrate and publish a sample FSM controller for bipedal locomotion and stable grasping of a rigid object by the HRP-5P humanoid robot in MuJoCo. The code and usage instructions for mc-mujoco, the developed robot modules, and the FSM controller are available online.