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Physical AI & Humanoid Robotics

A Complete 13-Week Program for Industry Professionals in Physical AI & Humanoid Robotics

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Why this textbook?🚀

A practical and structured pathway through Physical AI & Humanoid Robotics, designed to take you from fundamentals to real-world applications. Each module is carefully curated to include hands-on labs, interactive simulations, and industry-relevant projects, so you can learn by doing while building a strong foundation for advanced humanoid robotics development.

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Complete Curriculum

From ROS 2 fundamentals to advanced humanoid control — structured for progressive learning.

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Hands-on Projects

Practical labs and simulation exercises that bridge theory with real robotics workflows.

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Industry Ready

Focus on tools and patterns used in research & industry — ready to take to real projects.

Explore the 4-Module Learning Path

A hands-on curriculum guiding you from ROS 2 basics to VLA and humanoid robotics — with practical exercises and real-world examples.

Weeks 3-5

Module 1: The Robotic Nervous System (ROS 2)

Master ROS 2 architecture, communication patterns, and robot modeling. Learn to build distributed robotic systems using nodes, topics, services, and actions.

Learning Outcomes:
  • Explain the ROS 2 computation graph and its components
  • Create publishers, subscribers, and service clients using rclpy
  • Define robot structure using URDF and visualize in RViz2
Weeks 6-7

Module 2: Digital Twins - Simulation & Sensors

Build digital twins for robotic systems using Gazebo and Unity. Simulate sensors, physics, and environments for testing before deploying to physical hardware.

Learning Outcomes:
  • Create Gazebo simulation environments with physics and sensors
  • Integrate Unity for photorealistic sensor simulation
  • Test navigation and perception algorithms in simulation
Weeks 8-10

Module 3: NVIDIA Isaac - Perception & Navigation

Leverage NVIDIA Isaac Sim for GPU-accelerated robotics. Implement VSLAM, Nav2 navigation stacks, and reinforcement learning for autonomous behaviors.

Learning Outcomes:
  • Set up and configure NVIDIA Isaac Sim environments
  • Implement Visual SLAM for robot localization
  • Deploy Nav2 navigation stack for autonomous navigation
Weeks 11-13

Module 4: VLA & Humanoid Robotics

Integrate Vision-Language-Action models with humanoid robots. Master humanoid kinematics, manipulation, and conversational AI for natural human-robot interaction.

Learning Outcomes:
  • Calculate forward and inverse kinematics for humanoid robots
  • Implement manipulation primitives for pick-and-place tasks
  • Integrate conversational AI with robot action planning

Recent Updates

2025-11-29
Textbook Structure Initialized
Complete textbook structure with 4 modules and dashboard homepage is now live.
2025-11-29
Setup Guides Available
Hardware setup guides for Workstation, Edge Kit, and Cloud are now available.

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