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Learning Robotics using Python

You're reading from   Learning Robotics using Python Bring robotics projects to life with Python! Discover how to harness everything from Blender to ROS and OpenCV with one of our most popular robotics books.

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783287536
Length 330 pages
Edition 1st Edition
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Robotics 2. Mechanical Design of a Service Robot FREE CHAPTER 3. Working with Robot Simulation Using ROS and Gazebo 4. Designing ChefBot Hardware 5. Working with Robotic Actuators and Wheel Encoders 6. Working with Robotic Sensors 7. Programming Vision Sensors Using Python and ROS 8. Working with Speech Recognition and Synthesis Using Python and ROS 9. Applying Artificial Intelligence to ChefBot Using Python 10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python 11. Designing a GUI for a Robot Using Qt and Python 12. The Calibration and Testing of ChefBot Index

List of robotic vision sensors and image processing libraries


A 2D vision sensor or an ordinary camera delivers 2D image frames of the surroundings, whereas a 3D vision sensor delivers 2D image frames and an additional parameter called depth of each image point. We can find the x, y, and z distance of each point from the 3D sensor with respect to the sensor axis.

There are quite a few vision sensors available on the market. Some of the 2D and 3D vision sensors that can be used in our robot are mentioned in this chapter.

The following figure shows the latest 2D vision sensor called Pixy/CMU cam 5 (http://www.cmucam.org/), which is able to detect color objects with high speed and accuracy and can be interfaced to an Arduino board. Pixy can be used for fast object detection and the user can teach which object it needs to track. Pixy module has a CMOS sensor and NXP (http://www.nxp.com/) processor for image processing:

Pixy/CMU Cam 5

The commonly available 2D vision sensors are webcams. They contain...

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