Bridging Virtual and Physical Robotics: An AI-Driven Educational Platform Using NVIDIA Omniverse Isaac Sim and Jetson Orin Nano

This paper presents the development of a platform for educational robotics with artificial intelligence using NVIDIA Omniverse Isaac Sim, a custom robot based on NVIDIA Jetson Orin Nano and ROS2 (Robot Operating System 2) as a standardized development framework. Our research addresses the design and implementation of the system architecture for the platform, with the goal of being simple to use by the students, powerful enough to run machine learning algorithms faster than current state-of-theart platforms, and ensuring that students' code is transferable between virtual and physical environments. Previous research within the STEM area highlights multiple examples of using hardware such as Arduino boards or Raspberry Pi for educational robotics lacking the ability to run intensive machine learning algorithms on hardware such as NVIDIA Jetson Orin Nano. The proposed system architecture demonstrates NVIDIA Isaac Sim's potential in educational robotics by enabling students to experience how their own solutions operate in both virtual and physical learning environments.