Application of YOLO and Custom-Designed Intelligent Teaching Aids in Robotic Arm-Based Fruit Classification and Grasping Instruction - Chieh Wang, Chun; Sun-Jing Yan (International Journal of Computational and Experimental Science and Engineering, 2025)
With the growing impact of deep learning and computer vision, real-time image recognition and robotic systems have become increasingly important in fields such as autonomous vehicles and smart devices. In this study, a practical teaching module was developed by integrating the YOLO (You Only Look Once) algorithm, robotic arm control, and local crop recognition. The proposed system enables automated fruit detection, classification, and sorting using a six-axis robotic arm. This hands-on approach allows students to apply artificial intelligence in real-world agricultural contexts, thereby enhancing their understanding of smart farming technologies. The module supports both theoretical learning and skill development in automation and intelligent systems, aligning with future trends in AI-based agriculture and industrial applications.