Textbook Curriculum
A comprehensive 14-module journey through Physical AI and Humanoid Robotics
Introduction to Physical AI
Physical AI definition, embodiment, history, humanoids
Rigid Body Dynamics
Newton-Euler, forces, torques, inertia, momentum
Kinematics Fundamentals
Forward/inverse kinematics, DH parameters, workspaces
Sensors and Perception
IMU, cameras, LIDAR, sensor fusion, state estimation
Dynamics and Control
PID, computed torque, impedance control, stability
Motion Planning
RRT, A*, trajectory optimization, collision avoidance
Manipulation
Grasping, force control, dexterous manipulation
Locomotion
ZMP, whole-body control, bipedal walking, balance
ROS2 Integration
Nodes, topics, services, robot state, transforms
Simulation to Real
Domain randomization, reality gap, deployment
Learning-Based Control
RL, imitation learning, policy optimization
Human-Robot Interaction
Safety, collaboration, natural interfaces
Full-Body Autonomy
Integrated systems, decision making, autonomy
Capstone Integration
System design, deployment, future directions
Ready to Start Learning?
Begin with Module 01 or jump to your preferred learning path.
Learning Paths
Choose your focus area or follow the complete curriculum
Path A
Focus on dynamics, control theory, and manipulation. Ideal for robotics engineers and control specialists.
Path B
Focus on sensors, vision, planning, and human-robot interaction. Ideal for computer vision researchers.
Path C
Full-stack robotics covering all topics. Recommended for comprehensive understanding and capstone projects.