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PotoTwin Reinforcement Learning Examples

// repository documentation

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[Website](https://prototwin.com/) | [Documentation](https://prototwin.com/docs) | [Community Forum](https://community.prototwin.com/) | [Sign Up](https://prototwin.com/account/signup)

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      <h1>ProtoTwin Reinforcement Learning Examples</h1>
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---

ProtoTwin is an online simulation software for robotics and industrial automation. This repository provides a set of examples that you can use with ProtoTwin Connect to train RL agents. To run these example models, you will first need to create a ProtoTwin [account](https://prototwin.com/account/signup) and then download the ProtoTwin Connect desktop application. The following OS are supported:

- Windows 10/11 on x64 and Arm
- MacOS on Apple Silicon
- Linux on x64

## Clone Repository

Clone the repository by running the following command:

```
git clone https://github.com/prototwin/RLExamples.git
```

## Install Dependencies

You need to install the following Python packages:

```
pip install prototwin-gymnasium
pip install tensorboard
```

The [prototwin package](https://pypi.org/project/prototwin/) provides a client for starting and connecting to an instance of ProtoTwin Connect. This client may be used to issue commands to load a ProtoTwin model, step the simulation forward in time by one time-step, read signal values and write signal values.
The [prototwin gymnasium package](https://pypi.org/project/prototwin-gymnasium/) provides vectorized and non-vectorized base environments for Gymnasium.

## Examples

### CartPole V1

ProtoTwin single inverted pendulum (cartpole) tasked with swinging the pole up and balancing it.

To train the cartpole-v1 model:
```
cd cartpole-v1
python cartpole-v1.py
```

### CartPole V2

ProtoTwin cartpole v2 has reduced acceleration in the cart and domain randomization compared to v1 (designed for sim-to-real).

To train the cartpole-v2 model:
```
cd cartpole-v2
python cartpole-v2.py
```

### Bipedal Robot

ProtoTwin bipedal robot tasked with walking forward.

To train the bipedal model:
```
cd bipedal
python bipedal.py
```

### Quadruped Robot Handstand

Unitree Go2 quadruped robot tasked with performing a handstand.

To train the handstand model:
```
cd handstand
python handstand.py
```

### Robotic Ping Pong

uFactory xArm 6 robot tasked with bouncing a ping pong ball to the target height for as long as possible.

To train the pingpong model:
```
cd pingpong
python pingpong.py
```

### Quadrotor Drone

Quadrotor drone tasked with hovering to a randomly initialized target position marked by a yellow sphere.

To train the quadrotor model:
```
cd quadrotor
python quadrotor.py
```

RLExamples

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