Book Image

Artificial Vision and Language Processing for Robotics

By : Álvaro Morena Alberola, Gonzalo Molina Gallego, Unai Garay Maestre
Book Image

Artificial Vision and Language Processing for Robotics

By: Álvaro Morena Alberola, Gonzalo Molina Gallego, Unai Garay Maestre

Overview of this book

Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment.
Table of Contents (12 chapters)
Artificial Vision and Language Processing for Robotics
Preface

Introduction


Artificial Intelligence (AI) is changing everything. It tries to mimic human intelligence in order to achieve different tasks.

The section of AI that deals with images is called computer vision. Computer vision is an interdisciplinary scientific field that tries to mimic human eyes. It not only makes sense out of the pixels that are extracted from an image, but also gains a higher level of understanding from that specific image by performing automated tasks and using algorithms.

Some of these algorithms are better at object recognition, recognizing faces, classifying images, editing images, and even generating images.

This chapter will begin with an introduction to computer vision, starting with some of the most basic algorithms and an exercise to put them into practice. Later, an introduction to machine learning will be given, starting from the most basic algorithms to neural networks, involving several exercises to strengthen the knowledge acquired.