Intelligent Warehouse Robot for Classifying, Sorting, and Transporting Goods’ Boxes

With the rapid development of global retail e-commerce, the critical role of warehouses in logistics systems has become increasingly prominent. Current state-of-the-art solutions typically address only one or two warehouse tasks, including object recognition, sorting, and transportation. This paper presents the development of an integrated autonomous warehouse robot system capable of performing the three functions. The system mimics human capabilities by integrating various components, including advanced computer vision technologies using YOLOv5, a mobile robot, and a robotic arm. The YOLOv5 algorithm is employed for object detection and size estimation, enabling the system to classify goods-containing boxes into small, medium, and large categories. These classified goods are then delivered to predetermined locations by the mobile robot. Finally, the robot arm is employed to pick and place boxes in their storage location based on size. Experimental results demonstrate the system’s robustness and reliability, highlighting its significant potential to enhance warehouse management through robotic automation.