Book Image

Mastering ROS for Robotics Programming - Second Edition

By : Jonathan Cacace, Lentin Joseph
Book Image

Mastering ROS for Robotics Programming - Second Edition

By: Jonathan Cacace, Lentin Joseph

Overview of this book

In this day and age, robotics has been gaining a lot of traction in various industries where consistency and perfection matter. Automation is achieved via robotic applications and various platforms that support robotics. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications. This book focuses on the most stable release of ROS (Kinetic Kame), discusses advanced concepts, and effectively teaches you programming using ROS. We begin with aninformative overview of the ROS framework, which will give you a clear idea of how ROS works. During the course of this book, you’ll learn to build models of complex robots, and simulate and interface the robot using the ROS MoveIt! motion planning library and ROS navigation stacks. Learn to leverage several ROS packages to embrace your robot models. After covering robot manipulation and navigation, you’ll get to grips with the interfacing I/O boards, sensors, and actuators of ROS. Vision sensors are a key component of robots, and an entire chapter is dedicated to the vision sensor and image elaboration, its interface in ROS and programming. You’ll also understand the hardware interface and simulation of complex robots to ROS and ROS Industrial. At the end of this book, you’ll discover the best practices to follow when programming using ROS.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
www.PacktPub.com
Contributors
Preface
Index

Chapter 13. Using ROS in MATLAB and Simulink

In previous chapters, we discussed how to simulate and control robots implementing ROS nodes in C++. In this chapter, we will learn how to create ROS nodes using MATLAB, a powerful piece of software that provides several toolboxes with algorithms and hardware connectivity, for developing autonomous robotic applications for ground vehicles, manipulators, and humanoid robots. In addition, MATLAB integrates Simulink: a block diagram environment for model-based design, allowing the implementation of our control programs through a graphical editor. In this chapter, we will also discuss how to implement robotic applications using Simulink.

The first part of this chapter is dedicated to a brief introduction to MATLAB and the Robotic System Toolbox. After we have learned how to exchange data between ROS and MATLAB, we will implement an obstacle avoidance system for the differential drive mobile robot, Turtlebot, showing how simple it is to use components...