rl_sar/README.md

# rl_sar

[中文文档](README_CN.md)

Simulation verification and physical deployment of robot reinforcement learning algorithms, suitable for quadruped robots, wheeled robots, and humanoid robots. "sar" stands for "simulation and real"

## Preparation

Clone the code

```bash
git clone https://github.com/fan-ziqi/rl_sar.git
```

## Dependency

This project relies on ROS Noetic (Ubuntu 20.04)

After installing ROS, install the dependency library

```bash
sudo apt install ros-noetic-teleop-twist-keyboard ros-noetic-controller-interface  ros-noetic-gazebo-ros-control ros-noetic-joint-state-controller ros-noetic-effort-controllers ros-noetic-joint-trajectory-controller
```

Download and deploy `libtorch` at any location

```bash
cd /path/to/your/torchlib
wget https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-2.0.1%2Bcpu.zip
unzip libtorch-cxx11-abi-shared-with-deps-2.0.1+cpu.zip -d ./
echo 'export Torch_DIR=/path/to/your/torchlib' >> ~/.bashrc
```

Install yaml-cpp

```bash
git clone https://github.com/jbeder/yaml-cpp.git
cd yaml-cpp && mkdir build && cd build
cmake -DYAML_BUILD_SHARED_LIBS=on .. && make
sudo make install
sudo ldconfig
```

Install lcm

```bash
git clone https://github.com/lcm-proj/lcm.git 
cd lcm && mkdir build && cd build
cmake .. && make
sudo make install
sudo ldconfig
```

## Compilation

Customize the following two functions in your code to adapt to different models:

```cpp
torch::Tensor forward() override;
torch::Tensor compute_observation() override;
```

Then compile in the root directory

```bash
cd ..
catkin build
```

## Running

Before running, copy the trained pt model file to `rl_sar/src/rl_sar/models/YOUR_ROBOT_NAME`, and configure the parameters in `config.yaml`.

### Simulation

Open a new terminal, launch the gazebo simulation environment

```bash
source devel/setup.bash
roslaunch rl_sar gazebo_<ROBOT>.launch
```

Where \<ROBOT\> can be `a1` or `gr1t1`.

Press **0** on the keyboard to switch the robot to the default standing position, press **P** to switch to RL control mode, and press **1** in any state to switch to the initial lying position. WS controls x-axis, AD controls yaw, and JL controls y-axis.

Press **R** to reset Gazebo environment.

### Physical Robots

#### Unitree A1

Unitree A1 can be connected using both wireless and wired methods:

* Wireless: Connect to the Unitree starting with WIFI broadcasted by the robot **(Note: Wireless connection may lead to packet loss, disconnection, or even loss of control, please ensure safety)**
* Wired: Use an Ethernet cable to connect any port on the computer and the robot, configure the computer IP as 192.168.123.162, and the gateway as 255.255.255.0

Open a new terminal and start the control program

```bash
source devel/setup.bash
rosrun rl_sar rl_real_a1
```

Press the **R2** button on the controller to switch the robot to the default standing position, press **R1** to switch to RL control mode, and press **L2** in any state to switch to the initial lying position. The left stick controls x-axis up and down, controls yaw left and right, and the right stick controls y-axis left and right.

OR Press **0** on the keyboard to switch the robot to the default standing position, press **P** to switch to RL control mode, and press **1** in any state to switch to the initial lying position. WS controls x-axis, AD controls yaw, and JL controls y-axis.

## Add Your Robot

In the following, let ROBOT represent the name of your robot.

1. Create a model package named ROBOT_description in the robots folder. Place the URDF model in the urdf path within the folder and name it ROBOT.urdf. Create a namespace named ROBOT_gazebo in the config folder within the model file for joint configuration.
2. Place the model file in models/ROBOT.
3. Add a new field in rl_sar/config.yaml named ROBOT and adjust the parameters, such as changing the model_name to the model file name from the previous step.
4. Add a new launch file in the rl_sar/launch folder. Refer to other launch files for guidance on modification.
5. Change ROBOT_NAME to ROBOT in rl_xxx.cpp.
6. Compile and run.

## Reference

[unitree_ros](https://github.com/unitreerobotics/unitree_ros)

## Citation

Please cite the following if you use this code or parts of it:

```
@software{fan-ziqi2024rl_sar,
  author = {fan-ziqi},
  title = {{rl_sar: Simulation Verification and Physical Deployment of Robot Reinforcement Learning Algorithm.}},
  url = {https://github.com/fan-ziqi/rl_sar},
  year = {2024}
}
```