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

Introducing to Chefbot – a DIY mobile robot and its hardware configuration


In Chapter 6Using the ROS MoveIt! and Navigation Stack, we have discussed some mandatory requirements for interfacing a mobile robot with the ROS Navigation package. These requirements are recalled in the following:

  • Odometry source: The robot should publish its odometry/position data with respect to the starting position. The necessary hardware components that provide odometry information are wheel encoders, IMU, or 2D/3D cameras (visual odometry).
  • Sensor source: There should be a laser scanner, or a vision sensor that can act as a laser scanner. The laser scanner data is essential for the map-building process using SLAM.
  • Sensor transform using tf: The robot should publish the transform of the sensors and other robot components using ROS transform.
  • Base controller: The base controller is an ROS node, which can convert a twist message from the Navigation stack to corresponding motor velocities:

Figure 1: Chefbot prototype...