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Mastering Beaglebone Robotics

You're reading from   Mastering Beaglebone Robotics Master the power of the BeagleBone Black to maximize your robot-building skills and create awesome projects

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783988907
Length 234 pages
Edition 1st Edition
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Author (1):
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Richard Grimmett Richard Grimmett
Author Profile Icon Richard Grimmett
Richard Grimmett
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Table of Contents (13) Chapters Close

Preface 1. Preparing the BeagleBone Black FREE CHAPTER 2. Building a Basic Tracked Vehicle 3. Adding Sensors to Your Tracked Vehicle 4. Vision and Image Processing 5. Building a Robot that Can Walk 6. A Robot that Can Sail 7. Using GPS for Navigation 8. Measuring Wind Speed – Integrating Analog Sensors 9. An Underwater Remotely Operated Vehicle 10. A Quadcopter 11. An Autonomous Quadcopter Index

Using OpenCV


With your camera connected, you can access amazing vision capabilities that have been provided by the open source community. One of the most powerful capabilities is OpenCV.

You already installed OpenCV in Chapter 1, Preparing the BeagleBone Black. If you'd like a good overview on OpenCV and more documentation, see http://docs.opencv.org/.

Now you can try OpenCV. It is easiest to use Python when programming simple tasks, so let's start with the Python examples. If you prefer the C examples, they are also available. In order to use the Python examples, you'll need the python-numpy library. Type sudo apt-get install python-numpy. You will need this to manipulate the matrices that OpenCV uses to hold the images.

Start with one of the Python examples. You can access the Python examples by typing cd /home/ubuntu/examples/python. There are a number of useful examples; you'll start with the most basic. It is called camera.py. To run this example, you'll either need to have a display connected...

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