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Learning Robotics using Python

You're reading from   Learning Robotics using Python Design, simulate, program, and prototype an autonomous mobile robot using ROS, OpenCV, PCL, and Python

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788623315
Length 280 pages
Edition 2nd Edition
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Author (1):
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Lentin Joseph Lentin Joseph
Author Profile Icon Lentin Joseph
Lentin Joseph
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with Robot Operating System 2. Understanding the Basics of Differential Robots FREE CHAPTER 3. Modeling the Differential Drive Robot 4. Simulating a Differential Drive Robot Using ROS 5. Designing ChefBot Hardware and Circuits 6. Interfacing Actuators and Sensors to the Robot Controller 7. Interfacing Vision Sensors with ROS 8. Building ChefBot Hardware and the Integration of Software 9. Designing a GUI for a Robot Using Qt and Python 10. Assessments 11. Other Books You May Enjoy

Working with point clouds using Kinect, ROS, OpenNI, and PCL

A 3D point cloud is a way of representing a 3D environment and 3D objects as collection points along the x, y, and z axes. We can get a point cloud from various sources: Either we can create our point cloud by writing a program or we can generate it from depth sensors or laser scanners.

PCL supports the OpenNI 3D interfaces natively; thus, it can acquire and process data from devices (such as Prime Sensor's 3D cameras, Microsoft Kinect, or Asus Xtion Pro).

PCL will be included in the ROS full desktop installation. Let's see how we can generate and visualize a point cloud in RViz, a data visualization tool in ROS.

Opening the device and generating a point cloud

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