Book Image

BeagleBone Robotic Projects

By : Richard Grimmett
Book Image

BeagleBone Robotic Projects

By: Richard Grimmett

Overview of this book

Thanks to new, inexpensive microcontrollers, robotics has become far more accessible than it was in the past. These microcontrollers provide a whole new set of capabilities to allow even the most inexperienced users to make amazingly complicated projects. Beaglebone is effectively a small, light, cheap computer in a similar vein to Raspberry Pi and Arduino. It has all of the extensibility of today's desktop machines, but without the bulk, expense, or noise. This project guide provides step-by-step instructions to allow anyone to use this new, low cost platform in some fascinating robotics projects. By the time you are finished, your projects will be able to see, speak, listen, detect their surroundings, and move in a variety of amazing ways. The book begins with unpacking and powering up the components.This will include guidance on what to purchase and how to connect it all successfully–and a primer on programming the BeagleBone Black. Chapter by chapter, we will add additional software functionality available from the open source community, including how to make the system see using a webcam, how to hear using a microphone, and how to speak using a speaker. We then add hardware to make your robots move–including wheeled and legged examples–as well as covering how to add sonar sensors to avoid or find objects, plus wireless control to make your robot truly autonomous. Adding GPS allows the robot to find itself. Finally the book covers how to integrate all of this functionality so that it can all work together, before developing the most impressive robotics projects: those that can sail, fly, and explore underwater.
Table of Contents (18 chapters)
BeagleBone Robotic Projects
About the Author
About the Reviewers

Using the vision library to detect colored objects

Now that you have access to the OpenCV library, let's see what it can do.

Prepare for lift off

OpenCV and your webcam can track objects. This might be useful if you are building a system that needs to track and follow a colored ball. OpenCV makes this amazingly simple by providing some high-level libraries that can help you with this task. I'm going to do this in Python, as I find it much easier to work with than C. If you feel more comfortable in C, these instructions should be fairly easy to translate. Also, performance will be better if implemented in C, so you might create the initial capability in Python, and then finalize the code in C.

Engage thrusters

If you'd like, create a directory to hold your image-based work. From your home directory, create a directory named imageplay by typing mkdir imageplay. Then change directory to imageplay by typing cd imageplay.

Once there, let's bring over your file as a starting point by typing...