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Physical AI & Humanoid Robotics - Book Structure

This book is designed to be a comprehensive guide to the world of physical AI and humanoid robotics. It is structured into several modules, each focusing on a specific aspect of the field. The book is intended for students, researchers, and practitioners who are interested in understanding the principles and technologies behind humanoid robots.

Module 1: Foundations of AI and Robotics​

This module provides a solid foundation in the fundamental concepts of artificial intelligence and robotics.

  • Chapter 1: Introduction to Artificial Intelligence: A brief history of AI, its key concepts, and its applications.
  • Chapter 2: Machine Learning Fundamentals: An overview of supervised, unsupervised, and reinforcement learning.
  • Chapter 3: Introduction to Robotics: The basics of robot kinematics, dynamics, and control.
  • Chapter 4: Sensors and Actuators: The building blocks of robotic systems.
  • Chapter 5: Robot Operating System (ROS): A hands-on introduction to the most widely used robotics framework.

Module 2: Humanoid Robot Design and Control​

This module delves into the specifics of humanoid robot design and control, from the mechanical structure to the control algorithms.

  • Chapter 1: Humanoid Robot Kinematics and Dynamics: The mathematical models that describe the motion of humanoid robots.
  • Chapter 2: Bipedal Locomotion and Gait Generation: The challenges and techniques for making a robot walk like a human.
  • Chapter 3: Whole-Body Control: Coordinating the motion of the entire robot's body to perform complex tasks.
  • Chapter 4: Human-Robot Interaction: Designing robots that can safely and effectively interact with humans.
  • Chapter 5: Hardware Architecture of Humanoid Robots: A deep dive into the sensors, actuators, and computational hardware of modern humanoid robots.

Module 3: Perception and AI for Humanoid Robots​

This module explores how humanoid robots perceive the world and make intelligent decisions.

  • Chapter 1: Computer Vision for Humanoid Robots: Techniques for object recognition, tracking, and scene understanding.
  • Chapter 2: 3D Perception and SLAM: Simultaneous Localization and Mapping for autonomous navigation.
  • Chapter 3: Natural Language Processing for Human-Robot Interaction: Enabling robots to understand and respond to human language.
  • Chapter 4: Reinforcement Learning for Robot Control: Training robots to perform complex tasks through trial and error.
  • Chapter 5: Embodied AI and the Future of Humanoid Robotics: The concept of embodied intelligence and its implications for the future of AI.

Module 4: Applications and Future of Humanoid Robotics​

This module showcases the wide range of applications for humanoid robots and discusses the future of the field.

  • Chapter 1: Humanoid Robots in Healthcare: Assisting patients and medical staff in hospitals and homes.
  • Chapter 2: Humanoid Robots in Manufacturing and Logistics: Performing complex assembly and manipulation tasks.
  • Chapter 3: Humanoid Robots in Exploration and Disaster Response: Operating in hazardous environments where humans cannot go.
  • Chapter 4: Ethical and Social Implications of Humanoid Robotics: The societal impact of intelligent robots.
  • Chapter 5: The Future of Humanoid Robotics: A look at the next generation of humanoid robots and the challenges that lie ahead.

Appendices​

  • Appendix A: Mathematical Foundations: A refresher on linear algebra, calculus, and probability theory.
  • Appendix B: ROS Cheat Sheet: A quick reference guide to common ROS commands and tools.
  • Appendix C: Glossary of Terms: Definitions of key terms used in the book.