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Artificial Intelligence for Robotics

You're reading from   Artificial Intelligence for Robotics Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781805129592
Length 344 pages
Edition 2nd Edition
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Author (1):
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Francis X. Govers III Francis X. Govers III
Author Profile Icon Francis X. Govers III
Francis X. Govers III
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Building Blocks for Robotics and Artificial Intelligence
2. Chapter 1: The Foundation of Robotics and Artificial Intelligence FREE CHAPTER 3. Chapter 2: Setting Up Your Robot 4. Chapter 3: Conceptualizing the Practical Robot Design Process 5. Part 2: Adding Perception, Learning, and Interaction to Robotics
6. Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning 7. Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms 8. Chapter 6: Teaching a Robot to Listen 9. Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More
10. Chapter 7: Teaching the Robot to Navigate and Avoid Stairs 11. Chapter 8: Putting Things Away 12. Chapter 9: Giving the Robot an Artificial Personality 13. Chapter 10: Conclusions and Reflections 14. Answers 15. Index 16. Other Books You May Enjoy Appendix

What this book covers

Chapter 1, The Foundation of Robotics and Artificial Intelligence, explains what we will cover in this book, standard robot parts, concepts of control, computing in real time, and the Observe, Orient, Decide, Act (OODA) concept for how robots make decisions.

Chapter 2, Setting Up Your Robot, introduces you to motors, control systems, how to divide the robot problem into parts using the Subsumption Architecture, and the Robotics Operating System 2 (ROS 2).

Chapter 3, Conceptualizing the Practical Robot Design Process, describes systems engineering techniques for robot design, use cases, and storyboards.

Chapter 4, Recognizing Objects Using Neural Networks and Supervised Learning, explains how you can use CNNs to train object recognition and segment objects from the background.

Chapter 5, Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms, covers Q-learning and genetic algorithms, which are used to teach the robot arm to move efficiently.

Chapter 6, Teaching the Robot to Listen, shows you how you can add a digital assistant to your robot and create some custom controls for it, including telling knock-knock jokes.

Chapter 7, Teaching the Robot to Navigate and Avoid Stairs, outlines how you can use another CNN to teach the robot to navigate around a house and avoid obstacles.

Chapter 8, Putting Things Away, describes how we can finish the robot’s tasks, and how to find the toybox.

Chapter 9, Giving the Robot an Artificial Personality, explains the concepts and theory around simulating a personality in a robot for added interactions.

Chapter 10, Conclusions and Reflections, talks about robotics as a career, based on the author’s own 40-year career in robot design.

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