Physical AI & Humanoid Robotics
Welcome to the comprehensive textbook for Panaversity's Physical AI course. This 13-week curriculum covers the foundations of embodied intelligence, robot operating systems, simulation environments, and cutting-edge AI systems for humanoid robotics.
Course Overview
Physical AI represents the intersection of artificial intelligence with the physical world. Unlike purely digital AI systems, physical AI must navigate real-world constraints: physics, uncertainty, and real-time decision-making.
This textbook is organized into 5 modules:
Module 1: Introduction to Physical AI (Weeks 1-2)
Foundations of embodied intelligence, sensor systems (LiDAR, cameras, IMUs), and the advantages of humanoid form factors.
Module 2: ROS 2 Fundamentals (Weeks 3-5)
Robot Operating System 2 concepts including nodes, topics, services, actions, and URDF for humanoid robots.
Module 3: Simulation Environments (Weeks 6-7)
Gazebo physics simulation, Unity-based rendering, and sensor simulation for safe robot development.
Module 4: NVIDIA Isaac Platform (Weeks 8-10)
Isaac Sim, Isaac ROS with Visual SLAM, and Nav2 path planning for bipedal locomotion.
Module 5: Vision-Language-Action Systems (Weeks 11-13)
Voice-to-action pipelines, LLM-based cognitive planning, and a capstone project for autonomous humanoid behavior.
Instructor Overview
This section provides instructors with course planning resources.
13-Week Course Schedule
| Week | Module | Topics | Learning Hours |
|---|---|---|---|
| 1 | Module 1 | Physical AI foundations, sensor systems | 3 |
| 2 | Module 1 | Embodied intelligence, humanoid advantages | 3 |
| 3 | Module 2 | ROS 2 introduction, nodes and topics | 3 |
| 4 | Module 2 | Services, actions, parameters | 3 |
| 5 | Module 2 | URDF, TF2, launch files | 3 |
| 6 | Module 3 | Gazebo simulation basics | 3 |
| 7 | Module 3 | Unity rendering, sensor simulation | 3 |
| 8 | Module 4 | Isaac Sim introduction | 3 |
| 9 | Module 4 | Isaac ROS, Visual SLAM | 3 |
| 10 | Module 4 | Nav2, bipedal locomotion | 3 |
| 11 | Module 5 | VLA systems, voice-to-action | 3 |
| 12 | Module 5 | LLM cognitive planning | 3 |
| 13 | Module 5 | Capstone project presentations | 3 |
Total Contact Hours: 39 hours
Assessment Breakdown
| Component | Weight | Description |
|---|---|---|
| Weekly Exercises | 30% | Conceptual and coding exercises per chapter |
| Lab Assignments | 30% | Hands-on projects (one per module) |
| Midterm Project | 15% | Simulation-based robot navigation |
| Capstone Project | 25% | Autonomous humanoid behavior implementation |
Required Resources
- Linux workstation (Ubuntu 22.04 recommended)
- ROS 2 Humble installation
- NVIDIA GPU for Isaac Sim (RTX 3060+ recommended)
- GitHub Classroom for assignments
Prerequisites
Before starting this course, you should have:
- Python programming experience (intermediate level)
- Basic understanding of linear algebra (vectors, matrices)
- Familiarity with command-line interfaces
- Access to a computer capable of running ROS 2 and simulation software
How to Use This Textbook
Each chapter includes:
- Learning Objectives - What you'll be able to do after completing the chapter
- Conceptual Explanations - Theory and background
- Code Examples - Working code you can run and modify
- Exercises - Practice problems at different difficulty levels
- Summary - Key takeaways
Interactive Features
- AI Chatbot - Ask questions about any content using the chat widget
- Selection Q&A - Highlight any text to ask questions about it
- Progress Tracking - Track your progress through the course
Getting Started
Ready to begin? Start with Module 1: What is Physical AI?
This textbook is part of Panaversity's mission to provide world-class AI education.