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

Introduction to Chefbot- a DIY mobile robot and its hardware configuration


The following are the mandatory requirements for interfacing a mobile robot with ROS navigation package:

  • Odometry source: 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, and 2D/3D cameras (visual odometry).
  • Sensor source: There should be a laser scanner or a 3D vision sensor sensor, which can act as a laser scanner. The laser scanner data is essential for 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 a ROS node, which can convert a twist message from Navigation stack to corresponding motor velocities.

Figure 1: Chefbot prototype

We can check the components present in the robot and determine whether they satisfy the Navigation stack requirements...