Book Image

ROS Programming: Building Powerful Robots

By : Anil Mahtani, Aaron Martinez, Enrique Fernandez Perdomo, Luis Sánchez, Lentin Joseph
Book Image

ROS Programming: Building Powerful Robots

By: Anil Mahtani, Aaron Martinez, Enrique Fernandez Perdomo, Luis Sánchez, Lentin Joseph

Overview of this book

This learning path is designed to help you program and build your robots using open source ROS libraries and tools. We start with the installation and basic concepts, then continue with the more complex modules available in ROS, such as sensor and actuator integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, computer vision, perception in 3D with PCL, and more. We then discuss advanced concepts in robotics and how to program using ROS. You'll get a deep overview of the ROS framework, which will give you a clear idea of how ROS really works. During the course of the book, you will learn how to build models of complex robots, and simulate and interface the robot using the ROS MoveIt motion planning library and ROS navigation stacks. We'll go 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 beginner, intermediate, and expert ROS robotics applications inside! It includes content from the following Packt products: ? Effective Robotics Programming with ROS - Third Edition ? Mastering ROS for Robotics Programming ? ROS Robotics Projects
Table of Contents (37 chapters)
Title page
Copyright and Credits
Packt Upsell
Preface
Bibliography
Index

Image recognition using ROS and TensorFlow


After discussing the basics of TensorFlow, let's start discussing how to interface ROS and TensorFlow to do some serious work. In this section, we are going to deal with image recognition using these two.

There is a simple package to perform image recognition using TensorFlow and ROS. Here is the ROS package to do this:

https://github.com/qboticslabs/rostensorflow

This package was forked from https://github.com/OTL/rostensorflow. The package basically contains a ROS Python node that subscribes to images from the ROS webcam driver and performs image recognition using TensorFlow APIs. The node will print the detected object and its probability.

Note

This code was developed using TensorFlow tutorials from the following link: https://www.tensorflow.org/versions/r0.11/tutorials/image_recognition/index.html.

The image recognition is mainly done using a model called deep convolution network. It can achieve high accuracy in the field of image recognition. An...