Machine Vision and Datalogging Extension for the VEX Microprocessor using ESP-NOW

Robotics has become an important part of the academic curriculum from middle school up through university education. The VEX Robotics System is present and used in thousands of schools around the world for both competition and teaching. A hardware extension to the VEX Robotics System that permits real-time data logging and the use of machine vision will be presented. A hardware interface based on the ESP32 microprocessor and utilizing the ESP-NOW protocol will be described. Microcontroller programs written using the Arduino IDE, and an open-source graphical user interface written in Python will be discussed and are available for student use. Three practical classroom applications will be presented. The first is an object sorting machine that captures images using an OpenMV camera, utilizes the YoloV8 algorithm for object identification, and uses VEX hardware to physically sort objects into different bins. The second is a robot drivetrain repeatability laboratory that uses the system data logging capability to characterize path deviation from multiple robot runs. The third is a lift-and-hold experiment that allows students to explore proportional integral derivative control algorithm tuning. Additional system characteristics such as data packet transit time, machine vision computation times, and analysis of packet loss as a function of transmission distance will be presented. The system is shown to be well-suited for real-time object detection tasks and would make an excellent addition to any educational physics laboratory.