A cost-effective robot kit featuring an Arduino UNO Rev3 enhanced with obstacle-avoidance sensors and line-following capabilities can be transformed into a sophisticated face-tracking robot. The pivotal element in this upgrade lies in replacing the UNO Rev3 board with an Arduino UNO Q. The UNO Q board houses an STM32U585 microcontroller in addition to a Linux microprocessor, allowing for the integration of local artificial intelligence into the robot without necessitating any alterations to the mechanical components.
The project developed by Iulia Feroli showcases the seamless incorporation of local AI capabilities to a budget-friendly robot. The foundation of the robot is the Elegoo kit, equipped with a motor shield and sensors for obstacle avoidance and line following. By substituting the original board with the UNO Q and retaining the shield unaltered, the robot gains the ability to run machine learning models locally via the STM32 microcontroller and the Linux microprocessor, eliminating the need for a cloud connection.
To enable vision functionality, a standard USB webcam is connected to the UNO Q board. The webcam video stream undergoes processing using the face tracking Brick from Arduino App Lab. Through a code that translates facial positions in the frame into movement commands for the robot, the robot smoothly aligns itself with the detected face and moves toward it, ensuring it constantly faces the person in front. The resultant face tracker is highly responsive, operating independently without any reliance on external servers or Wi-Fi connections.
Iulia Feroli’s project is detailed in a video demonstration showcasing the robot in action, including a thorough explanation of the assembly process and coding involved. The key modification lies in replacing the UNO Rev3 with the UNO Q, a strategic choice that maintains electrical and mechanical compatibility while introducing the necessary computing power for AI functions.
This innovative project emphasizes the simplicity of transforming a basic robot into a sophisticated face tracker with local AI capabilities. The UNO Q board, combining the efficiency of the STM32U585 microcontroller with the processing power of the Linux processor, enables the execution of machine learning models like face tracking without requiring additional hardware. The board is available in a 4GB variant with a comprehensive accessory kit, facilitating easy adoption for aspiring robot enthusiasts.
While the original Elegoo kit with the Arduino UNO Rev3 remains a versatile platform for various projects, the UNO Q proves to be the ideal choice for implementing a face tracker due to its enhanced computing power and seamless compatibility with the motor shield. Despite the advanced features introduced, the overall cost of the project remains budget-friendly, culminating in a smart and responsive robot.
In conclusion, by leveraging readily available components such as the Elegoo kit, a USB webcam, and the UNO Q control board, enthusiasts can replicate this intelligent face-tracking robot with ease. The UNO Q acts as the heart of the system, amalgamating the simplicity of the STM32U585 microcontroller with the robustness of the Linux processor, enabling advanced functionalities like face tracking without the need for external hardware.
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