Speed Control Technology Using Image Processing Method for an Autonomous Electric Go-Kart

Abstract

This thesis explores the design and implementation of a speed control system for an autonomous electric Go-Kart using computer vision. It addresses the challenges of safety, efficiency, and reliability in autonomous vehicle technology. The study covers the evolution, advancements in autonomous vehicles and sensor technologies. The main objective is to create a system that uses face detection to control the Go-Kart’s speed, ensuring safe object tracking. The research involves using a Raspberry Pi, Logitech webcam, and Arduino Pro Mini, with Python and OpenCV for face detection. Results show successful face detection and speed adjustment, contributing to safer autonomous systems. The study suggests further improvements, such as additional sensors and advanced algorithms, to enhance system robustness and efficiency.