<div align="center"> <h1>RoboJuDo 🤖</h1>

A plug-and-play deploy framework for robots. Just deploy, just do.

<h3> 🔗 RoboJuDo is part of the FRoM-W1 project, check it out at 👉 <a href="https://github.com/OpenMOSS/FRoM-W1"> OpenMOSS / FRoM-W1 </a> </h3> <p>  <a href="https://github.com/HansZ8/RoboJuDo/releases"> <img src="https://img.shields.io/github/v/release/HansZ8/RoboJuDo?color=blue&label=version" alt="release"/> </a>  <img src="https://img.shields.io/badge/platform-Windows%20%7C%20Ubuntu-green" alt="platform"/>  <img src="https://img.shields.io/badge/robot-UnitreeG1%20%7C%20UnitreeH1%20%7C%20FFTAIgr1-orange" alt="multi-robot"/>  <img src="https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white]" alt="pre-commit"/>  <a href="https://creativecommons.org/licenses/by-nc/4.0/"> <img src="https://img.shields.io/badge/License-CC--BY--NC--4.0-lightgrey.svg" alt="license"/> </a> </p> <img src="docs/images/header-demo.gif" width="80%" alt="demo"/> <br> <br> </div>

Tired of projects that release only models but no deployment code? RoboJuDo provides a unified framework that makes policy deployment straightforward and practical.

Our framework highlights:

Out-of-the-box: After setting up RoboJudo, multiple policies can be deployed on both simulation and real robots in minutes: Quick Start.
Decoupled & Modular Design: With a Python-first design, RoboJuDo makes fast prototyping easy. Environment, Controller, and Policy are modular and freely composable, while minimal code changes allow seamless adaptation across robots and setups: See how we achieve this: Add a new module.
Multi-policy switching: Seamlessly switch between different policies during a task. Try this: Multi-Policy Switching.
Light-Weight: Our framework is lightweight, after 5 minutes of setup, it runs smoothly onboard. By UnitreeCpp, RoboJuDo runs on Unitree G1 without the need for an Ethernet cable.

📓Content

📄Introduction
🛠️Easy Setup
📖Quick Start
🧩 Develop and Contribute

🗺️Roadmap

2026.03 Update: We added built-in support for deploying the ProtoMotions G1 tracker in RoboJuDo. Thanks to NVLabs for the great work on ProtoMotions, and thanks to Chen Tessler and Yifeng Jiang for contributing this integration.

[x] [2025.04] Initialized project
[x] [2025.05] Add support for Unitree G1
[x] [2025.05] Add support for Unitree H1, FFTAI Gr1T1
[x] [2025.06] Integrated Unitree C++ SDK
[x] [2025.08] Add support for beyondmimic
[x] [2025.09] RoboJuDo Opensource 🎉
[x] [2025.10] Add support for ASAP
- [x] Implement deepmimic and locomotion, check AsapPolicy!
- [x] Preserve original keyboard and joystick mappings
- [x] Support for KungfuBot
[x] Add policy-switch pipeline with interpolation, check LocoMimic Example!
[x] [2025.11] Add support for KungfuBot2 , check KungfuBotGeneralPolicy!
[x] [2025.11] Add support for TWIST , check TwistPolicy!
[x] [2026.03] Add support for ProtoMotions ✨, check ProtoMotions Tracker and ProtoMotionsTrackerPolicy!
[ ] Release code for HugWBC
[ ] Release code for GMT
[ ] Upcoming policies...

</td> <td width="20%"> <div align="center"> <img src="docs\images\job.gif" alt="working" width="100%" > </div> </td> </table>

📄Introduction

This repository provides a deployment framework for humanoid robots, supporting the use of different policies across different environments (real robots and simulation).
We decouple the controller, environment, and policy, making it easy for users to add their own policies or environments.
Experiment configurations can be organized through config files.

The main modules of RoboJuDo consist of:

🎮 Controller: A collection of control signals. It receives external inputs (e.g., joystick, keyboard, motion sequences) and forwards them as ctrl_data to the pipeline.
🤖 Environment: The execution environment (e.g., Mujoco, real robot). It processes actions provided by the policy and sends real-time sensor data as env_data to the pipeline.
🌐 Policy: A trained control policy (from various wbc & locomotion works). It generates actions based on information from both the environment and the controller.

Currently, RoboJuDo supports the following policy–environment combinations:

| Policy | Unitree G1 | Unitree H1 | FFTAI gr1t1 | Ref | Doc | Feature & Note | |:-------:|:--------:|:-------:|:-------:|:-------:|:-------:|:-------:| | Unitree Official | 🖥️ 🤖 | 🖥️ 🤖 | - | unitree_rl_gym | UnitreePolicy| | | Unitree Wo Gait | 🖥️ 🤖 | - | - | unitree_rl_lab | UnitreeWoGaitPolicy| no gait | | Human2Humanoid | 🖥️ 🤖 | 🖥️ 🤖 | 🖥️ | H2H | H2HStudentPolicy | Need PHC submodule | | Smooth | 🖥️ 🤖 | 🖥️ 🤖 | 🖥️ 🤖⚠️ | Smooth | | | AMO | 🖥️ 🤖 | - | - | AMO | AmoPolicy | | | GMT | 🖥️ 🤖 | - | - | GMT | | | | HugWBC | 🖥️ 🤖 | 🖥️ 🤖 | - | HugWBC | HugWbcPolicy | | | BeyondMimic | 🖥️ 🤖 | - | - | whole_body_tracking | BeyondmimicPolicy | With&Wo SE supported | | ASAP | 🖥️ 🤖 | - | - | ASAP | AsapPolicy | deepmimic & locomotion supported | | KungfuBot<br>KungfuBot2 | 🖥️ 🤖 | - | - | PBHC | AsapPolicy<br>KungfuBotGeneralPolicy | Need PHC submodule | | TWIST | 🖥️ 🤖 | - | - | TWIST | TwistPolicy | | | ProtoMotions | 🖥️ 🤖 | - | - | ProtoMotions | ProtoMotionsTrackerPolicy | nvlab doc | | ... | ... | ... | ... | ... | ... | ... |

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🖥️ means policy is ready for simulation, while 🤖 means policy has been tested on real robot.

🛠️Easy Setup

RoboJuDo supports multiple platforms, officially tested on Ubuntu, macOSand Windows.

Robot onboard PCs are also supported.

1️⃣ Basic Installation

Step 1: Clone the repository and create a Python environment

git clone https://github.com/HansZ8/RoboJuDo.git
cd RoboJuDo/
# Example using conda
conda create -n robojudo python=3.11 -y
conda activate robojudo

Step 2: Install RoboJuDo

# Optional, install cpu version for speed up
pip install torch --index-url https://download.pytorch.org/whl/cpu
pip install -e .

2️⃣ Install Optional Modules

RoboJuDo is a plug-and-play framework. After a minimal default installation, you can selectively configure and install only the modules you need.

Step 0: [Optional] Install Robot SDK

You can skip this for sim2sim and development.

If you plan to control a real robot, install the corresponding SDK.

For example, see unitree_setup.md for Unitree robots.

Step 1: Configure modules

Edit submodule_cfg.yaml to select modules, by setting install as true.

As default, mujoco_viewer is selected for sim2sim.

Step 2: Install modules

# Install all required modules
python submodule_install.py

# Or specify modules to install with args
# python submodule_install.py unitree_cpp

📖Quick Start

RoboJuDo is a modular framework where tasks can be flexibly defined by composing configuration files.
In the following, we use the deployment on G1 as an example.

Run Sim2Sim
Run Sim2Real
Deploy More Policies✨

Run RoboJuDo on Simulation

Begin your journey with unitree g1 sim2sim.

A Xbox controller is needed for control.

# run the default g1 sim2sim cfg
python scripts/run_pipeline.py

You can control the motivation using any Xbox

RoboJuDo

Install / Use

README