Tesla Optimus and the Impact of Humanoid Robotics on the Engineering Profession
 

Course Description:

This course provides Professional Engineers with a comprehensive examination of humanoid robotics through a systems engineering lens. It explores the technical foundations required to design and evaluate such systems, including mechanical load management, energy storage and distribution, sensor fusion, real-time control, and AI-enabled software behavior. Particular emphasis is placed on how these elements interact and how design decisions in one domain influence safety, reliability, and operational feasibility across the system.

Learning Objectives:

Upon completion of this course, the Professional Engineer will be able to:

1. Explain the defining characteristics of humanoid robotic systems and how they differ from traditional fixed and mobile automation used in industrial environments.
2. Describe the integrated systems architecture of a humanoid robot, including mechanical structures, electrical and power systems, sensors, control systems, artificial intelligence, and software layers.
3. Evaluate mechanical and structural engineering challenges associated with humanoid robots, including dynamic stability, joint actuation, fatigue life, materials selection, and fail-safe mechanical design.
4. Assess electrical and power system requirements for humanoid robots, including onboard energy storage, power distribution, thermal management, fault protection, and electrical safety considerations.
5. Analyze sensor, perception, and control system design considerations, including sensor fusion, real-time feedback, human–robot interaction, and safe operation in unstructured environments.
6. Distinguish between AI-driven and rule-based software behavior in humanoid robots and evaluate the implications for system predictability, validation, and engineering oversight.
7. Identify appropriate engineering applications for humanoid robots across manufacturing, infrastructure inspection, utilities, and construction environments, recognizing technical constraints and operational boundaries.