Vision-Guided Pick and Place Systems Using Raspberry Pi and YOLO

Abstract

Vision-guided pick and place systems have revolutionized various industrial and robotic applications by enabling efficient automation and enhancing productivity. This paper introduces a vision-guided pick and place system merging Raspberry Pi and the YOLO (You Only Look Once) algorithm. By integrating Raspberry Pi’s affordability and versatility with YOLO’s real-time object detection, the system achieves accurate and prompt identification of objects for manipulation. The architecture incorporates Raspberry Pi with cameras and robotic arms, enabling seamless object detection and manipulation. Implementation details encompass software development and hardware setup to ensure smooth integration and optimal performance. Experimental validation confirms robust object detection capabilities, even under challenging conditions. Real-time performance analysis underscores the system’s suitability for dynamic industrial environments necessitating swift decision-making and precise manipulation. This approach offers a cost-effective, scalable solution for industrial automation, promising heightened productivity, reduced manual intervention, and enhanced operational efficiency across manufacturing and logistics sectors.