Go2Py/README.md

# Go2Py

Go2Py is a Pythonic interface and driver for low-level and high-level control of Unitree Go2 quadruped robots. The motivation of this project is to ease the burden of initial interface development, safety systems of Go2 quadruped by providing a modular pipeline for real-time communication with the robot in both simulated and real world with a unified interface. 

<p align="center">
  <img src="docs/assets/openfig.png" alt="image" width="60%" height="auto"/>
</p>

This project is comprised of the following components:
- **C++ Bridge:** A dockerized ROS2 bridge built upon the [unitree_ros2](https://github.com/unitreerobotics/unitree_ros2) that implements a remote controlled emergency stop and publishes the robot states as standard ROS2 topics usable by upstream systems such as NAV2. 
- **Robot Interface:** A simple Python class that represents the robot and communicates with the C++ bridge through either DDS (ROS independent) or ROS2 interfaces. 
- **Robot Management FSM:** A finite state machine for controlling the behavior of the robot up to the point of handover to the user low-level controller (sitting down, standing up) with safety monitors (motor temperatures, emergency stops).
- **Robot Model:** A simple to use [Pinocchio](https://github.com/stack-of-tasks/pinocchio) wrapper for computing the kinematics and dynamics parameters of the robot. 
- **Simulation Interface:** Simulation environments based on Mujoco and Nvidia Orbit (To be added) with a Python interface identical to the real robot. 

## How Does Using it Look Like?
Communication with the robot will be as simple as importing a Python class:
```python
from Go2Py.robot.interface.dds import GO2Real
from Go2Py.robot.model import Go2Model
robot = GO2Real(mode='lowlevel')
model = Go2Model()
robot.standDownReset()
while running:
    joint_state = robot.getJointStates()
    imu = robot.getIMU()
    remote = robot.getRemoteState()
    model.update(state['q'], state['dq'],T,vel) # T and vel from the EKF
    info = model.getInfo()
    
    #User control computations ...

    robot.setCommands(q_des, dq_des, kp, kd, tau_ff)
```
An identical workflow is can be followed for simulation:
```python
from Go2Py.sim.mujoco import Go2Sim
from Go2Py.robot.model import Go2Model
robot = Go2Sim()
model = Go2Model()
robot.standDownReset()
while running:
    joint_state = robot.getJointStates()
    imu = robot.getIMU()
    remote = robot.getRemoteState()
    model.update(state['q'], state['dq'],T,vel) # T and vel from the EKF
    info = model.getInfo()

    #User control computations ...

    robot.setCommands(q_des, dq_des, kp, kd, tau_ff)
    robot.step()
```
## Installation
Follow through the steps in here to [setup](docs/setup.md) the robot and Go2Py. 

## Further Examples 
A set of sorted examples are provided in the [examples](examples) directory to get you up and running quickly:

- High-level body velocity interface (ROS2)
- High-level body velocity interface (DDS)
- Low-level joint interface (ROS2)
- Low-level joint interface (DDS)
- Low-level simulation interface
- Contact Force Estimation 
- Foot Contact Estimation
- Extended Kalman Filter Legged Inertial State Estimator
- Walk These Ways RL Controller