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

Chapter 10. Point Clouds

Point clouds appeared in the robotics toolbox as a way to intuitively represent and manipulate the information provided by 3D sensors, such as time-of-flight cameras and laser scanners, in which the space is sampled in a finite set of points in a 3D frame of reference. The Point Cloud Library (PCL) provides a number of data types and data structures to easily represent not only the points of our sampled space, but also the different properties of the sampled space, such as color and normal vectors. PCL also provides a number of state-of-the-art algorithms to perform data processing on our data samples, such as filtering, model estimation, and surface reconstruction.

ROS provides a message-based interface through which PCL point clouds can be efficiently communicated, and a set of conversion functions from native PCL types to ROS messages, in much the same way as it is done with OpenCV images. Aside from the standard capabilities of the ROS API, there are a number...