Fully Automated Paper Document Sorting Robot Design

Abstract

A fully automated paper document sorting robot was developed in this project. This robot classifies documents efficiently and accurately. The objective of this project was to improve the efficiency of classifying or sorting paper documents, reduce costs, and save time. The robot can classify documents according to user-defined rules, such as keywords, dates, serial numbers, bar codes, and the meaning of paragraphs. Since it can classify or sort documents intelligently, it can complete large-scale document classification quickly. The robot is constructed using an aluminum profile to create a box-type truss gantry structure frame. It was built on the LubanCat 4 motherboard and controlled through Python language programming. Driven by a stepper motor to move the manipulator. The camera module is combined with an artificial intelligence algorithm to recognize paper in real time, and the text is recognized after taking pictures of the paper. The sorting function is performed by several sensors. In addition, a web-based human-computer interaction platform was developed using the Flask web framework in Python. Users could access this platform in a variety of ways, allowing them to easily and swiftly configure parameters and send operational instructions to perform various functions.