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Learning ROS for Robotics Programming Second Edition

You're reading from   Learning ROS for Robotics Programming Second Edition Take control of the Linux based Robot Operating System, and discover the tools, libraries, and conventions you need to create your own robots without the hassle.

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Product type Paperback
Published in Aug 2015
Publisher Packt
ISBN-13 9781783987580
Length 458 pages
Edition 1st Edition
Languages
Tools
Concepts
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Authors (2):
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 Mahtani Mahtani
Author Profile Icon Mahtani
Mahtani
Aaron Martinez Aaron Martinez
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Aaron Martinez
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Table of Contents (27) Chapters Close

Learning ROS for Robotics Programming Second Edition
Credits
About the Author
Acknowledgments
About the Author
Acknowledgments
About the Author
Acknowledgments
About the Author
Acknowledgments
About the Reviewer
About the Reviewer
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started with ROS Hydro FREE CHAPTER 2. ROS Architecture and Concepts 3. Visualization and Debug Tools 4. Using Sensors and Actuators with ROS 5. Computer Vision 6. Point Clouds 7. 3D Modeling and Simulation 8. The Navigation Stack – Robot Setups 9. The Navigation Stack – Beyond Setups 10. Manipulation with MoveIt! Index

Summary


In this chapter we have explored the different tools, algorithms and interfaces which can be used to work with point clouds in ROS. The reader might have noticed that we have tried to link the examples together to provide more insight into how these kinds of nodes might be used in a reusable manner. In any case, given the computational price of point cloud processing, any kind of architectural design will be inextricably linked to the computational capabilities of the system at hand.

The data flow of our examples should start with all of the data producers, which are the pcl_create and the pcl_read. It should continue to the data filters which are the pcl_filter and the pcl_downsampling. After the filtering is performed, more complex information can be extracted through the pcl_planar_segmentation, pcl_partitioning and pcl_matching. Finally, the data can be written to disk through the pcl_write or visualized through the pcl_visualize.

The main objective of this particular chapter was...

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