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Mastering ROS for Robotics Programming, Third edition - Third Edition

You're reading from   Mastering ROS for Robotics Programming, Third edition - Third Edition Best practices and troubleshooting solutions when working with ROS

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Product type Book
Published in Oct 2021
Publisher Packt
ISBN-13 9781801071024
Pages 594 pages
Edition 3rd Edition
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Concepts
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Authors (2):
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Mr. Lentin Joseph Mr. Lentin Joseph
Author Profile Icon Mr. Lentin Joseph
Mr. Lentin Joseph
Jonathan Cacace Jonathan Cacace
Author Profile Icon Jonathan Cacace
Jonathan Cacace
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Table of Contents (22) Chapters Close

Preface 1. Section 1 – ROS Programming Essentials
2. Chapter 1: Introduction to ROS FREE CHAPTER 3. Chapter 2: Getting Started with ROS Programming 4. Section 2 – ROS Robot Simulation
5. Chapter 3: Working with ROS for 3D Modeling 6. Chapter 4: Simulating Robots Using ROS and Gazebo 7. Chapter 5: Simulating Robots Using ROS, CoppeliaSim, and Webots 8. Chapter 6: Using the ROS MoveIt! and Navigation Stack 9. Chapter 7: Exploring the Advanced Capabilities of ROS MoveIt! 10. Chapter 8: ROS for Aerial Robots 11. Section 3 – ROS Robot Hardware Prototyping
12. Chapter 9: Interfacing I/O Board Sensors and Actuators to ROS 13. Chapter 10: Programming Vision Sensors Using ROS, OpenCV, and PCL 14. Chapter 11: Building and Interfacing Differential Drive Mobile Robot Hardware in ROS 15. Section 4 – Advanced ROS Programming
16. Chapter 12: Working with pluginlib, nodelets, and Gazebo Plugins 17. Chapter 13: Writing ROS Controllers and Visualization Plugins 18. Chapter 14: Using ROS in MATLAB and Simulink 19. Chapter 15: ROS for Industrial Robots 20. Chapter 16: Troubleshooting and Best Practices in ROS 21. Other Books You May Enjoy

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...

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