Book Image

ROS Programming: Building Powerful Robots

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

ROS Programming: Building Powerful Robots

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

Overview of this book

This learning path is designed to help you program and build your robots using open source ROS libraries and tools. We start with the installation and basic concepts, then continue with the more complex modules available in ROS, such as sensor and actuator integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, computer vision, perception in 3D with PCL, and more. We then discuss advanced concepts in robotics and how to program using ROS. You'll get a deep overview of the ROS framework, which will give you a clear idea of how ROS really works. During the course of the book, you will learn how to build models of complex robots, and simulate and interface the robot using the ROS MoveIt motion planning library and ROS navigation stacks. We'll go through great projects such as building a self-driving car, an autonomous mobile robot, and image recognition using deep learning and ROS. You can find beginner, intermediate, and expert ROS robotics applications inside! It includes content from the following Packt products: ? Effective Robotics Programming with ROS - Third Edition ? Mastering ROS for Robotics Programming ? ROS Robotics Projects
Table of Contents (37 chapters)
Title page
Copyright and Credits
Packt Upsell
Preface
Bibliography
Index

Visualizing nodes diagnostics


ROS nodes can provide diagnostic information using the diagnostics topic. For that, there is an API that helps to publish diagnostic information in a standard way. The information follows the diagnostic_msgs/DiagnosticStatus message type, which allows us to specify a level (OK, WARN, ERROR), name, message, and hardware ID as well as a list of diagnostic_msgs/KeyValue, which are pairs of key and value strings.

The interesting part comes with the tools that collect and visualize this diagnostic information. At the basic level, rqt_runtime_monitor allows us to visualize the information directly published through the diagnostics topic. Run the example7 node, which publishes information through the diagnostics topic, and this visualization tool, to see the diagnostic information:

    $ roslaunch chapter3_tutorials example7.launch
    $ rosrun rqt_runtime_monitor rqt_runtime_monitor
  

The previous commands display the following output:

When the system is large, we can...