TWO-WHEEL ELECTRIC BALANCING BASED ON STEERING CONTROL AND MACHINE VISION

The travel method of vehicles is mostly performed with fuel energy from gasoline, which causes problems with pollution to the environment.This research proposes the electric energy of two-wheel electric balancing (TWEB) based on steering control and machine vision.The design of usability applies a 14-inch 350-watt DC brushless motor with two wheels to handle a load of 80 kilograms.The steering control is a PID controller with a gyroscope sensor model MPU6050, which measures angular and acceleration velocity with a rotary encoder 600 pulses/revolution.PID control increases performance with the Kalman filter.The rest of the autonomous moving indoors with machine vision uses machine learning with a board Raspberry Pi Model 4B, feeding images from a webcam.Custom dataset from training within an indoor environment based on YOLOv8 performs mode autonomous moving.Pre-processing with Bluetooth, self-balancing mode, prepares for autonomous indoor navigation.The proposed method also features self-balancing with a PID control, as shown in a graph, which can respond with time minimized.TWEB with steering control and machine vision is simple and improves to support future usage better than the traditional method.