Book Image

ROS Robotics Projects

Book Image

ROS Robotics Projects

Overview of this book

Robot Operating System is one of the most widely used software frameworks for robotic research and for companies to model, simulate, and prototype robots. Applying your knowledge of ROS to actual robotics is much more difficult than people realize, but this title will give you what you need to create your own robotics in no time! This book is packed with over 14 ROS robotics projects that can be prototyped without requiring a lot of hardware. The book starts with an introduction of ROS and its installation procedure. After discussing the basics, you’ll be taken through great projects, such as building a self-driving car, an autonomous mobile robot, and image recognition using deep learning and ROS. You can find ROS robotics applications for beginner, intermediate, and expert levels inside! This book will be the perfect companion for a robotics enthusiast who really wants to do something big in the field.
Table of Contents (20 chapters)
ROS Robotics Projects
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Functional block diagram of a typical self-driving car


The following shows the important components of a self-driving vehicle. The list of parts and their functionalities will be discussed in this section. We'll also look at the exact sensor that was used in the autonomous car for the DARPA Challenge.

Figure 4: Important components of a self-driving car

GPS, IMU, and wheel encoders

As you know, the Global Positioning System (GPS) helps us determine the global position of a vehicle with the help of GPS satellites. The latitude and longitude of the vehicle can be calculated from the GPS data. The accuracy of GPS can vary with the type of sensor; some sensors have an error in the range of meters, and some have less than 1 meter of error. We can find vehicle state by combining GPS, inertial measurement unit (IMU) and wheel odometry data, and by using sensor fusion algorithms. This can give better estimate of the vehicle. Let's look at the position estimation modules used for the DARPA Challenge...