Design method for intelligent robots applied to traditional CNC processing plants: An integrated system based on mechanical, circuit, and image recognition technologies

This study aims to design an automated production assistance device for small to medium-sized traditional CNC factories. The goal is to provide a cost-effective auxiliary production tool that integrates seamlessly into existing machining environments. The design encompasses mechanical, circuit, and software components. Mechanically, the device features a robotic arm equipped with a camera for object recognition and gripping, utilizing real-time image processing to enhance efficiency and stability. The circuit design employs embedded devices and microcontrollers to create a low-power, high-performance control system that manages motor drive, sensor data collection, and image recognition. On the software front, the system uses OpenCV and You Only Look Once (YOLO) for object detection and identification to tackle complex industrial scenarios. The design also considers economic feasibility, making it suitable for effective application in small and medium-sized enterprises. Through detailed theoretical analysis and multi-stage system simulations, the intelligent robot system has been thoroughly validated for overall stability and practicality. The final product is an intelligent self-propelled cart with capabilities, supporting efficient automated production and the intelligent upgrade of traditional manufacturing industries. Such a system is expected to significantly enhance production line efficiency in variable environments, reduce reliance on manual labor, and promote the intelligent transformation of traditional factories.