Creating a GUI for Robot State Visualization and Control using Gazebo Harmonic, ROS2 Jazzy, and PyQt

In the world of robotics, visualizing the state of a robot and being able to control it is crucial for development and testing purposes. In this tutorial, we will walk you through how to create a graphical user interface (GUI) for robot state visualization and control using Gazebo Harmonic, ROS2 Jazzy, and PyQt.

Step 1: Install Gazebo Harmonic and ROS2 Jazzy
Before we can start creating our GUI, we need to make sure we have Gazebo Harmonic and ROS2 Jazzy installed on our system. You can follow the installation instructions on the official Gazebo and ROS websites to install these tools on your machine.

Step 2: Create a ROS2 package
Once you have Gazebo and ROS2 installed, it’s time to create a new ROS2 package for our project. Open a terminal and run the following command to create a new ROS2 package called "robot_gui":

ros2 pkg create --build-type ament_python robot_gui

Step 3: Create a Qt GUI using PyQt
Next, we will create a GUI using PyQt, a popular Python library for creating desktop applications with a graphical interface. To install PyQt, you can run the following command:

pip install PyQt5

Now, let’s create a new Python file called "robot_gui.py" in the "src" directory of our ROS2 package. This file will contain our PyQt GUI code. Here is an example of a simple GUI layout:

import sys
from PyQt5.QtWidgets import QApplication, QWidget, QPushButton

class RobotGUI(QWidget):
    def __init__(self):
        super().__init__()
        self.initUI()

    def initUI(self):
        self.setWindowTitle('Robot GUI')
        self.setGeometry(100, 100, 400, 300)

        btn_start = QPushButton('Start', self)
        btn_start.move(50, 50)

        btn_stop = QPushButton('Stop', self)
        btn_stop.move(50, 100)

        self.show()

if __name__ == '__main__':
    app = QApplication(sys.argv)
    gui = RobotGUI()
    sys.exit(app.exec_())

Step 4: Integrate Gazebo with PyQt GUI
Now that we have created a basic PyQt GUI, we can integrate it with Gazebo to visualize the robot state and control it. We will use the Gazebo API to communicate with the simulation environment from our PyQt application.

First, we need to install the necessary Python packages to interact with Gazebo:

pip install ros2_gazebo
pip install rclpy gazebo_ros_py

Next, we can import the Gazebo API into our PyQt application and use it to retrieve the robot’s state and send control commands. Here is an example of how you can integrate Gazebo with our PyQt GUI:

import rclpy
from rclpy.node import Node
from gazebo_ros_py.gazebo_interface import GazeboInterface

class RobotControllerNode(Node):
    def __init__(self):
        super().__init__('robot_controller')
        self.gazebo = GazeboInterface()

    def get_robot_state(self):
        robot_state = self.gazebo.get_model_state('robot')
        return robot_state

    def set_robot_position(self, x, y, z):
        self.gazebo.set_model_state('robot', x, y, z)

def main(args=None):
    rclpy.init(args=args)
    node = RobotControllerNode()
    rclpy.spin(node)
    rclpy.shutdown()

if __name__ == '__main__':
    main()

In this example, we have created a new ROS2 node called "RobotControllerNode" that uses the GazeboInterface class to interact with Gazebo. We can call the get_robot_state() method to retrieve the robot’s current state and the set_robot_position() method to control the robot’s position in the simulation.

Step 5: Launch the GUI and Gazebo simulation
To run our PyQt GUI and connect it with the Gazebo simulation, we need to launch both the GUI and the simulation environment. First, we need to build our ROS2 package by running the following commands:

colcon build
source install/setup.bash

Next, we can launch our PyQt GUI and Gazebo simulation by running the following commands in separate terminals:

ros2 run robot_gui robot_gui.py
ros2 launch gazebo_ros_py gazebo.launch.py

Congratulations! You have successfully created a GUI for robot state visualization and control using Gazebo Harmonic, ROS2 Jazzy, and PyQt. You can now expand on this project by adding more features to the GUI and integrating additional functionalities with Gazebo. Happy robot developing!