Book Image

Effective Robotics Programming with ROS - Third Edition

By : Anil Mahtani, Luis Sánchez, Aaron Martinez, Enrique Fernandez Perdomo
Book Image

Effective Robotics Programming with ROS - Third Edition

By: Anil Mahtani, Luis Sánchez, Aaron Martinez, Enrique Fernandez Perdomo

Overview of this book

Building and programming a robot can be cumbersome and time-consuming, but not when you have the right collection of tools, libraries, and more importantly expert collaboration. ROS enables collaborative software development and offers an unmatched simulated environment that simplifies the entire robot building process. This book is packed with hands-on examples that will help you program your robot and give you complete solutions using open source ROS libraries and tools. It also shows you how to use virtual machines and Docker containers to simplify the installation of Ubuntu and the ROS framework, so you can start working in an isolated and control environment without changing your regular computer setup. It starts with the installation and basic concepts, then continues with more complex modules available in ROS such as sensors and actuators integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, Computer Vision, perception in 3D with PCL, and more. By the end of the book, you’ll be able to leverage all the ROS Kinetic features to build a fully fledged robot for all your needs.
Table of Contents (18 chapters)
Effective Robotics Programming with ROS Third Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Visualizing the camera input images with rqt_image_view


In Chapter 3, Visualization and Debugging Tools, we explained how to visualize any image published in the ROS framework by using the image_view node of the image_view package or rqt_image_view. The following code encapsulates this discussion:

$ rosrun image_view image_view image:=/camera/image_raw

What is important here is the fact that by using the image transport, we can select different topics for viewing images using compressed formats if required. Also, in the case of stereo vision, as we will see later, we can use rqt rviz to see the point cloud obtained with the disparity image.