# 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:

```bash
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:

```bash
~/miniconda3/bin/conda init --all
source ~/.bashrc
```

### 1.2 Create a New Environment

Use the following command to create a virtual environment:

```bash
conda create -n unitree-rl python=3.8
```

### 1.3 Activate the Virtual Environment

```bash
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:

```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 Isaac Gym

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

#### 2.2.1 Download

Download [Isaac Gym](https://developer.nvidia.com/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:

```bash
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:

```bash
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 Install

```bash
cd rsl_rl
pip install -e .
```

### 2.4 Install go2_rl_gym

#### 2.4.1 Download

Clone the repository using Git:

```bash
git clone https://github.com/unitreerobotics/go2_rl_gym.git
```

#### 2.4.2 Install

Navigate to the directory and install it:

```bash
cd go2_rl_gym
pip install -e .
```

### 2.5 Install unitree_cpp_deploy (Optional)

Refer to our C++ deployment repository, which is based on unitree_rl_lab and specifically designed for deploying models trained in this repository: [unitree_cpp_deploy](https://github.com/wty-yy-mini/unitree_cpp_deploy).