Artificial Intelligence for Robotics : Build Intelligent Robots Using ROS 2, Python, OpenCV, and AI/ML Techniques for Real-World Tasks / Francis X. Govers and Kamesh Namuduri.

Format:

Book

Author/Creator:

Govers, Francis X., author.

Namuduri, Kamesh, author.

Language:

English

Subjects (All):

Artificial intelligence.

Robotics.

Physical Description:

1 online resource (344 pages)

Edition:

Second edition.

Place of Publication:

Birmingham, England : Packt Publishing Ltd., [2024]

Biography/History:

Govers Francis X. : Francis X. Govers III is an Associate Technical Fellow for Autonomy at Bell Textron, and chairman of the Textron Autonomy Council. He is the designer of over 30 unmanned vehicles and robots for land, sea, air, and space, including RAMSEE, the autonomous security guard robot. Francis helped lead the design of the International Space Station, the F-35 JSF Fighter, the US Army Future Combat Systems, and telemetry systems for NASCAR and IndyCar. He is an engineer, pilot, author, musician, artist, and maker. He received five outstanding achievement awards from NASA and recognition from Scientific American for World Changing Ideas. He has a Master of Science degree from Brandeis University and is a veteran of the US Air Force.

Summary:

Unlock the potential of your robots by enhancing their perception with cutting-edge artificial intelligence and machine learning techniques. From neural networks to computer vision, this book equips you with the tools and practical use cases to create truly smart robots. Starting with robotics basics, robot architecture, control systems, and decision-making theory, this book presents systems-engineering methods to design problem-solving robots with single-board computers. You’ll explore object recognition and genetic algorithms to teach your robot to identify and pick up objects, and you'll also harness the power of natural language processing to give your robot a voice. To enhance your robot further, you’ll master neural networks to classify and separate objects and navigate autonomously, before advancing to guiding your robot arms using reinforcement learning and genetic algorithms. The book also covers path planning and goal-oriented programming to prioritize your robot's tasks, showing you how to connect all software using Python and ROS 2 for a seamless experience. By the end of this book, you’ll have learned how to transform your robot into a helpful assistant with NLP and give it an artificial personality, ready to tackle real-world tasks and even crack jokes.

Contents:

Cover

Title Page

Copyright and Credits

Foreword

Contributors

Table of Contents

Preface

Part 1: Building Blocks for Robotics and Artificial Intelligence

Chapter 1: The Foundation of Robotics and Artificial Intelligence

Technical requirements

The basic principle of robotics and AI

What is AI and autonomy (and what is it not)?

Are recent developments in AI anything new?

What is a robot?

Our sample problem - clean up this room!

The basics of robotics

The techniques used in this book

When do you need AI for your robot?

Introducing the robot and our development environment

Software components (ROS, Python, and Linux)

Robot control systems and a decision-making framework

Summary

Questions

Further reading

Chapter 2: Setting Up Your Robot

Understanding the anatomy of a robot

Introducing subsumption architecture

A brief introduction to ROS

Hardware and software setup

Preparing the laptop

Chapter 3: Conceptualizing the Practical Robot Design Process

A systems engineering-based approach to robotics

Understanding our task - cleaning up the playroom

Use cases

Our robot's task - part 1

Our robot's task - part 2

What is our robot to do?

Using storyboards

Storyboard - put away the toys

Project goals

Understanding the scope of our use case

Identifying our hardware needs

Breaking down our software needs

Writing a specification

Part 2: Adding Perception, Learning, and Interaction to Robotics

Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning

A brief overview of image processing

Understanding our object recognition task

Image manipulation

Convolution.

Artificial neurons

Training a CNN

Using YOLOv8 - an object recognition model

Understanding how to train our toy detector

Building the toy detector

Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms

Task analysis

Designing the software

Setting up the solution

Machine learning for robot arms

How do we pick actions?

Creating the interface to the arm

Introducing Q-learning for grasping objects

Writing the code

Introducing GAs

Understanding how the GA process works

Building a GA process

Alternative robot arm ML approaches

Google's SAC-X

Amazon Robotics Challenge

Chapter 6: Teaching a Robot to Listen

Exploring robot speech recognition with NLP

Briefly introducing the NLP concept

Setting our goals

Understanding the STT process

Clarifying the intent

Programming our robot

Setting up the hardware

Setting up the Mycroft software

Adding skills

Part 3: Advanced Concepts - Navigation, Manipulation, Emotions, and More

Chapter 7: Teaching the Robot to Navigate and Avoid Stairs

Understanding the SLAM methodology

Exploring alternative navigation techniques

Introducing the Floor Finder technique

Implementing neural networks

Processing the image

Training the neural network for navigation

CNN robot control implementation

Chapter 8: Putting Things Away

Introducing decision trees

What do we mean by pruning?

Creating self-classifying decision trees

Understanding entropy.

Implementing one-hot encoding

Random forests

Introducing robot path planning

Understanding the coordinate system

Developing a map based on our knowledge

Introducing the A* algorithm

Introducing the D* (D-star or dynamic A*) algorithm

GPS path finding

Chapter 9: Giving the Robot an Artificial Personality

What is an artificial personality?

A brief introduction to the (obsolete) Turing test, chatbots, and generative AI

The art and science of simulation

An emotion state machine

Playing the emotion game

Creating a model of human behavior

Integrating an artificial personality into our robot

Constructing a personality

Adding context

Under construction

Developing the robot emotion engine

Creating a human emotion model

Creating human information storage

Context memory

Chapter 10: Conclusions and Reflections

Learning when to stop

Careers in robotics

Exploring the current state of AI

Looking ahead in AI and robotics

Is AI phobia reasonable?

Comparing the needs of humans and AI

Understanding risk in AI

Answers

Appendix

Introducing MOSA

A brief overview of ROS 2

Understanding the basic concepts

Comparing ROS 2 and ROS

Software requirements for the robot

Installing ROS 2

Installing other packages

Basic ROS 2 commands

Introducing the hardware for the robot

Effectors - base, motors, and wheels

Battery

DC/DC power supply

CPU - the brains of the outfit

Effectors - robot arm

Arm controller

Arduino microcontroller and motor controller

Sensor - USB camera

Sensor and effector - audio interface

Robot safety tips

Index

Other Books You May Enjoy.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

ISBN:

9781805124399

1805124390

OCLC:

1429162884