h12_loco_manipulation

Prerequisites

• Ubuntu 22.04 Operating System
• IsaacGym Preview 4.0
  • NVIDIA GPU (RTX 4070 )
  • NVIDIA GPU Driver (Driver Version: 570.124.06 CUDA Version: 12.8 )

Installation Guide

System Requirements

• Operating System: Recommended Ubuntu 18.04 or later
• GPU: Nvidia GPU
• Driver Version: Recommended version 525 or later

0. Create a New Environment

Use the following command to create a virtual environment:

conda create -n unitree_rl python=3.8

Activate the Virtual Environment

conda activate unitree_rl

1. Installing Dependencies

1.1 Install PyTorch

conda install pytorch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 pytorch-cuda=12.1 -c pytorch -c nvidia

1.2 Install Isaac Gym

Isaac Gym is a rigid body simulation and training framework provided by Nvidia.

Download

Download Isaac Gym from Nvidia’s official website.

Install

After extracting the package, navigate to the isaacgym/python folder and install it using the following commands:

cd isaacgym/python
pip install -e .

1.3 Install rsl_rl

Download

Clone the repository using Git:

git clone https://github.com/leggedrobotics/rsl_rl.git

Switch Branch

Switch to the v1.0.2 branch:

cd rsl_rl
git checkout v1.0.2

Install

pip install -e .

2. Install h12_loco_manipulation

Download

Clone the repository using Git:

git clone https://github.com/correlllab/h12_loco_manipulation.git

Install

Navigate to the directory and install it:

cd h12_loco_manipulation
pip install -r requirements

Install unitree_sdk2py (Optional ~ For Real Deployment)

unitree_sdk2py is a library used for communication with real robots. If you need to deploy the trained model on a physical robot, install this library.

Download

Clone the repository using Git:

git clone https://github.com/unitreerobotics/unitree_sdk2_python.git

Install

Navigate to the directory and install it:

cd unitree_sdk2_python
pip install -e .

Then you can follow the README.md in each sub-repostory to install all three parts or just one of them.

📄 License

Acknowledgements

• OpenHomie: We use OpenHomie library as our codebase.
• RSL_RL: We use rsl_rl library to train the control policies for legged robots.
• Legged_gym: We use legged_gym library to train the control policies for legged robots.
• Unitree SDK2 Python : We use Unitree SDK2 Python library from Unitree to control the real robot.