Book Image

Mastering ROS for Robotics Programming, Third edition - Third Edition

By : Lentin Joseph, Jonathan Cacace
Book Image

Mastering ROS for Robotics Programming, Third edition - Third Edition

By: Lentin Joseph, Jonathan Cacace

Overview of this book

The Robot Operating System (ROS) is a software framework used for programming complex robots. ROS enables you to develop software for building complex robots without writing code from scratch, saving valuable development time. Mastering ROS for Robotics Programming provides complete coverage of the advanced concepts using easy-to-understand, practical examples and step-by-step explanations of essential concepts that you can apply to your ROS robotics projects. The book begins by helping you get to grips with the basic concepts necessary for programming robots with ROS. You'll then discover how to develop a robot simulation, as well as an actual robot, and understand how to apply high-level capabilities such as navigation and manipulation from scratch. As you advance, you'll learn how to create ROS controllers and plugins and explore ROS's industrial applications and how it interacts with aerial robots. Finally, you'll discover best practices and methods for working with ROS efficiently. By the end of this ROS book, you'll have learned how to create various applications in ROS and build your first ROS robot.
Table of Contents (22 chapters)
1
Section 1 – ROS Programming Essentials
4
Section 2 – ROS Robot Simulation
11
Section 3 – ROS Robot Hardware Prototyping
15
Section 4 – Advanced ROS Programming

Developing a simple control system in Simulink

Now that we have learned how to interface Simulink and ROS, we can try to implement a more complex system that is able to control a real or simulated robot. We will continue to work with the TurtleBot robot simulated in Gazebo, and we will see how to control its orientation to bring it to the desired value. In other words, we will implement a control system that will measure the orientation of the robot using its odometry, comparing this value with the desired orientation and obtaining the orientation error. We will use a PID controller to calculate the velocity to actuate the robot to reach the final desired orientation, setting the orientation error to 0. This controller is already available in Simulink, so we don't need to implement it by ourselves. Let's start to discuss all the elements of our model:

Figure 14.23 – TurtleBot orientation control model in Simulink

The input of the system is...