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You're reading from ROS Robotics Projects Make your robots see, sense, and interact with cool and engaging projects with Robotic Operating System

Product type Paperback

Published in Mar 2017

Publisher Packt

ISBN-13 9781783554713

Length 452 pages

Edition 1st Edition

Languages

C++

Tools

ROS

Concepts

Robotics

Author (1):

Lentin Joseph

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Table of Contents (20) Chapters

ROS Robotics Projects

Credits

About the Author

Acknowledgements

About the Reviewer

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Preface

1. Getting Started with ROS Robotics Application Development FREE CHAPTER

2. Face Detection and Tracking Using ROS, OpenCV and Dynamixel Servos

3. Building a Siri-Like Chatbot in ROS

4. Controlling Embedded Boards Using ROS

5. Teleoperate a Robot Using Hand Gestures

6. Object Detection and Recognition

7. Deep Learning Using ROS and TensorFlow

8. ROS on MATLAB and Android

9. Building an Autonomous Mobile Robot

10. Creating a Self-Driving Car Using ROS

11. Teleoperating a Robot Using a VR Headset and Leap Motion

12. Controlling Your Robots over the Web

Setting Robotics Toolbox in MATLAB

Here is the link to download a trial or purchase the Robotics Toolbox in MATLAB (https://in.mathworks.com/products/robotics.html). This toolbox is compatible with MATLAB version 2013 onward. If you don't have MATLAB, you can test the chapter's code using a trial version; if you have it, buy or download a trial version of Robotic Toolbox.

Basic ROS functions in MATLAB

After setting up Robotics Toolbox in MATLAB, we can start working on the important functions of MATLAB that are used to interact with a ROS network. Let's look at them with examples.

Initializing a ROS network

Before running a ROS node, we have to run the roscore command, right? The roscore command will start a ROS master, and other ROS nodes can find each other through it. In MATLAB, instead of the roscore command, we can use the rosinit function to start a ROS master.