3.5 KiB
Installation Guide
System Requirements
- Operating System: Recommended Ubuntu 18.04 or later
- GPU: Nvidia GPU
- Driver Version: Recommended version 525 or later
1. Creating a Virtual Environment
It is recommended to run training or deployment programs in a virtual environment. Conda is recommended for creating virtual environments. If Conda is already installed on your system, you can skip step 1.1.
1.1 Download and Install MiniConda
MiniConda is a lightweight distribution of Conda, suitable for creating and managing virtual environments. Use the following commands to download and install:
mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh
After installation, initialize Conda:
~/miniconda3/bin/conda init --all
source ~/.bashrc
1.2 Create a New Environment
Use the following command to create a virtual environment:
conda create -n unitree-rl python=3.8
1.3 Activate the Virtual Environment
conda activate unitree-rl
2. Installing Dependencies
2.1 Install PyTorch
PyTorch is a neural network computation framework used for model training and inference. Install it using the following command:
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 Isaac Gym
Isaac Gym is a rigid body simulation and training framework provided by Nvidia.
2.2.1 Download
Download Isaac Gym from Nvidia’s official website.
2.2.2 Install
After extracting the package, navigate to the isaacgym/python folder and install it using the following commands:
cd isaacgym/python
pip install -e .
2.2.3 Verify Installation
Run the following command. If a window opens displaying 1080 balls falling, the installation was successful:
cd examples
python 1080_balls_of_solitude.py
If you encounter any issues, refer to the official documentation at isaacgym/docs/index.html.
2.3 Install rsl_rl
rsl_rl is a library implementing reinforcement learning algorithms.
2.3.1 Download
Clone the repository using Git:
git clone https://github.com/leggedrobotics/rsl_rl.git
2.3.2 Switch Branch
Switch to the v1.0.2 branch:
cd rsl_rl
git checkout v1.0.2
2.3.3 Install
pip install -e .
2.4 Install unitree_rl_gym
2.4.1 Download
Clone the repository using Git:
git clone https://github.com/unitreerobotics/unitree_rl_gym.git
2.4.2 Install
Navigate to the directory and install it:
cd unitree_rl_gym
pip install -e .
2.5 Install unitree_sdk2py (Optional)
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.
2.5.1 Download
Clone the repository using Git:
git clone https://github.com/unitreerobotics/unitree_sdk2_python.git
2.5.2 Install
Navigate to the directory and install it:
cd unitree_sdk2_python
pip install -e .
Summary
After completing the above steps, you are ready to run the related programs in the virtual environment. If you encounter any issues, refer to the official documentation of each component or check if the dependencies are installed correctly.