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Physical AI & Humanoid Robotics Textbook

Welcome to a comprehensive 13-week course covering the fundamentals of Physical AI, ROS 2, robot simulation, NVIDIA Isaac platform, and Vision-Language-Action (VLA) systems.

What You Will Learn​

This course is structured into 4 modules spanning 13 weeks:

Module 1: Introduction to Physical AI & ROS 2 (Weeks 1-5)​

Learn the foundations of embodied intelligence and master ROS 2 for robotics development.

  • Week 1: Physical AI Foundations - Embodied intelligence, sensor-actuator loops, real-world applications
  • Week 2: Embodied Intelligence Deep Dive - Perception-action coupling, environmental interaction
  • Week 3: ROS 2 Basics - Architecture, nodes, workspaces, packages
  • Week 4: ROS 2 Communication - Topics, services, actions, parameters
  • Week 5: ROS 2 Package Development - Package structure, launch files, build system

Module 2: Robot Simulation (Weeks 6-7)​

Explore Gazebo and Unity for realistic robot simulation environments.

  • Week 6: Gazebo Simulation - Setup, URDF/SDF formats, physics simulation
  • Week 7: Unity Robotics - Unity integration, ROS-Unity communication

Module 3: NVIDIA Isaac Platform (Weeks 8-10)​

Dive into Isaac SDK and Isaac Sim for perception, reinforcement learning, and sim-to-real transfer.

  • Week 8: Isaac SDK Introduction - Architecture, modules, codelets
  • Week 9: Isaac Sim & Perception - Sensor simulation, perception systems
  • Week 10: Reinforcement Learning & Sim-to-Real Transfer - RL for robot control, transfer techniques

Module 4: Humanoid Robotics & VLA (Weeks 11-13)​

Study humanoid kinematics, bipedal locomotion, and cutting-edge VLA systems.

  • Week 11: Humanoid Kinematics - Forward/inverse kinematics, degrees of freedom
  • Week 12: Bipedal Locomotion & Balance - Gait generation, balance control, zero-moment point
  • Week 13: Vision-Language-Action Systems - Multimodal AI, VLA systems, conversational robotics

Getting Started​

Navigate to Week 1: Physical AI Foundations to begin your learning journey.

Prerequisites​

  • Basic understanding of AI/ML concepts
  • Python programming experience
  • Familiarity with Linux command line (helpful but not required)

Course Structure​

Each week follows a consistent structure:

  • Learning Objectives: What you'll achieve
  • Core Concepts: Key technical concepts
  • Practical Explanation: Detailed explanations with examples
  • Visual Aids: Diagrams and illustrations
  • Summary: Key takeaways and next steps

How to Use This Textbook​

  1. Sequential Learning: Start with Week 1 and progress through each week in order
  2. Modular Study: Each week is self-contained - you can revisit specific topics as needed
  3. Hands-On Practice: Code examples are provided throughout - try them yourself
  4. Additional Resources: Links to official documentation and external resources are included

Built by Sabeh Shaikh © 2025