Init
This commit is contained in:
119
doc/setup_en.md
Normal file
119
doc/setup_en.md
Normal file
@@ -0,0 +1,119 @@
|
||||
# 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).
|
||||
Reference in New Issue
Block a user