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RoboMimic Deploy is a multi-policy robot deployment framework based on a state-switching mechanism. Currently, the included policies are designed for the Unitree G1 robot (29-DoF).
## Preface - **This deployment framework is only applicable to G1 robots with a 3-DOF waist. If a waist fixing bracket is installed, it must be unlocked according to the official tutorial before this framework can be used normally.** - **It is recommended to remove the hands, as dance movements may cause interference.** - **When deploying real robots, if something goes wrong, it's probably the policy's fault—not your hardware. Don't waste time second-guessing your robot's physical setup.** - **[video instruction](https://www.bilibili.com/video/BV1VTKHzSE6C/?vd_source=713b35f59bdf42930757aea07a44e7cb#reply114743994027967)** ## Installation and Configuration ## 1. Create a Virtual Environment It is recommended to run training or deployment programs in a virtual environment. We suggest using Conda to create one. ### 1.1 Create a New Environment Use the following command to create a virtual environment: ```bash conda create -n robomimic python=3.8 ``` ### 1.2 Activate the Virtual Environment ```bash conda activate robomimic ``` --- ## 2. Install Dependencies ### 2.1 Install PyTorch PyTorch is a neural network computation framework used for model training and inference. Install it with the following command: ```bash conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia ``` ### 2.2 Install RoboMimic_Deploy #### 2.2.1 Download Clone the repository via git: ```bash git clone https://github.com/ccrpRepo/RoboMimic_Deploy.git ``` #### 2.2.2 Install Components Navigate to the directory and install: ```bash cd RoboMimic_Deploy pip install numpy==1.20.0 pip install onnx onnxruntime ``` #### 2.2.3 Install unitree_sdk2_python ```bash git clone https://github.com/unitreerobotics/unitree_sdk2_python.git cd unitree_sdk2_python pip install -e . ``` --- ## Running the Code ## 1. Run Mujoco Simulation ```bash python deploy_mujoco/deploy_mujoco.py ``` ## 2. Policy Descriptions | Mode Name | Description | |------------------|-----------------------------------------------------------------------------| | **PassiveMode** | Damping protection mode | | **FixedPose** | Position control reset to default joint values | | **LocoMode** | Stable walking control mode | | **Dance** | Charleston dance routine | | **KungFu** | Martial arts movement | | **KungFu2** | Failed martial arts training | | **Kick** | Bad mimic policy | | **SkillCast** | Lower body + waist stabilization with upper limbs positioned to specific joint angles (typically executed before Mimic strategy) | | **SkillCooldown**| Lower body + waist continuous balancing with upper limbs reset to default angles (typically executed after Mimic strategy) | --- ## 3. Operation Instructions in Simulation 1. Connect an Xbox controller. 2. Run the simulation program: ```bash python deploy_mujoco/deploy_mujoco.py ``` 3. Press the Start button to enter position control mode. 4. Hold R1 + A to enter LocoMode, then press BACKSPACE in the simulation to make the robot stand. Afterward, use the joystick to control walking. 5. Hold R1 + X to enter Dance mode—the robot will perform the Charleston. In this mode: - Press Select at any time to switch to damping protection mode. - Hold R1 + A to return to walking mode (not recommended). - Press Start to return to position control mode. 6. The terminal will display a progress bar for the dance. After completion, press R1 + A to return to normal walking mode. 7. In LocoMode, pressing R1 + Y triggers a Martial arts movement — use only in simulation. 8. In LocoMode, pressing L1 + Y triggers a Martial arts movement(Failed) — use only in simulation. 9. In LocoMode, pressing R1 + B triggers a Kick movement(Failed) — use only in simulation. --- ## 4. Real Robot Operation Instructions 1. Power on the robot and suspend it (e.g., with a harness). and then hold L2+R2 2. Run the deploy_real program: ```bash python deploy_real/deploy_real.py ``` 3. Press the Start button to enter position control mode. 4. Subsequent operations are the same as in simulation. --- ## Important Notes ### 1. Framework Compatibility Notice The current framework does not natively support deployment on G1 robots equipped with Orin NX platforms. Preliminary analysis suggests compatibility issues with the `unitree_python_sdk` on Orin systems. For onboard Orin deployment, we recommend the following alternative solution: - Replace with [unitree_sdk2](https://github.com/unitreerobotics/unitree_sdk2) (official C++ SDK) - Implement a dual-node ROS architecture: - **C++ Node**: Handles data transmission between robot and controller - **Python Node**: Dedicated to policy inference ### 2. Mimic Policy Reliability Warning The Mimic policy does not guarantee 100% success rate, particularly on slippery/sandy surfaces. In case of robot instability: - Press `F1` to activate **PassiveMode** (damping protection) - Press `Select` to immediately terminate the control program ### 3. Charleston Dance (R1+X) - Stable Policy Notes Currently the only verified stable policy on physical robots: ⚠️ **Important Precautions**: - **Palm Removal Recommended**: The original training didn't account for palm collisions (author's G1 lacked palms) - **Initial/Final Stabilization**: Brief manual stabilization may be required when starting/ending the dance - **Post-Dance Transition**: While switching to **Locomotion/PositionControl/PassiveMode** is possible, we recommend: - First transition to **PositionControl** or **PassiveMode** - Provide manual stabilization during transition ### 4. Other Movement Advisories All other movements are currently **not recommended** for physical robot deployment. ### 5. Strong Recommendation **Always** master operations in simulation before attempting physical robot deployment.