This paper presents an autonomous vehicle system's design, development, and programming process utilizing QR code-based positioning and navigation technology. During system development, the STM32F407 microcontroller is employed to control two motors with integrated encoders, where the PID controller and trapezoidal velocity control method are applied to optimize operational performance. The microcontroller processes data received from the embedded computer and provides feedback via the Universal Asynchronous Receiver Transmitter (UART) protocol. The system integrates a Raspberry Pi 4 embedded computer to process QR code information via a USB camera, receive commands from a remote control interface, and transmit control signals to the microcontroller after analyzing QR code data. Additionally, the system is designed to relay feedback to the control centre, ensuring precise and stable operation. Experimental results demonstrate that the autonomous vehicle can move at a stable speed of...
This paper presents an autonomous vehicle system's design, development, and programming process utilizing QR code-based positioning and navigation technology. During system development, the STM32F407 microcontroller is employed to control two motors with integrated encoders, where the PID controller and trapezoidal velocity control method are applied to optimize operational performance. The microcontroller processes data received from the embedded computer and provides feedback via the Universal Asynchronous Receiver Transmitter (UART) protocol. The system integrates a Raspberry Pi 4 embedded computer to process QR code information via a USB camera, receive commands from a remote control interface, and transmit control signals to the microcontroller after analyzing QR code data. Additionally, the system is designed to relay feedback to the control centre, ensuring precise and stable operation. Experimental results demonstrate that the autonomous vehicle can move at a stable speed of 0.3 m/s, with an optimal QR code spacing of 0.6 m. Furthermore, the control interface was successfully developed, validating the feasibility of QR code-based positioning and navigation for autonomous vehicles.