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


Natural Language Processing (NLP) is an area of Artificial Intelligence (AI) with the goal of enabling computers to understand and manipulate human language in order to perform useful tasks. Within this area, there are two sections: Natural Language Understanding (NLU) and Natural Language Generation (NLG).

In recent years, AI has changed the way machines interact with humans. AI helps people solve complex equations by performing tasks such as recommending a movie according to your tastes (recommender systems). Thanks to the high performance of GPUs and the huge amount of data available, it's possible to create intelligent systems that are capable of learning and behaving like humans.

There are many libraries that aim to help with the creation of these systems. In this chapter, we will review the most famous Python libraries to extract and clean information from raw text. You may consider this task complex, but a complete understanding and interpretation of the language is a difficult...