Design of Control System for Handling, Sorting, and Warehousing Robot Based on Machine Vision

摘要

With the introduction of the “Industry 4.0” concept, the fourth industrial revolution, centered on intelligent manufacturing, has gained global momentum. Within automated production systems built upon industrial robots, the integration of machine vision to enhance system intelligence has become a prominent research focus. This project encompasses the design of a machine vision-based control system for handling, sorting, and warehousing robots. Key components include control circuit design, hardware selection, and the development of algorithms for extracting and recognizing workpiece image features. The project employs teaching pendant programming commands for path planning of the mechanical arm, enabling tasks such as fixture manipulation and precise workpiece handling. A position sensor is utilized to track workpiece positions, facilitating the coordinated operation of push cylinders, conveyors, and the mechanical arm. A workflow involving “camera capture - color measurement - conditional detection - data transmission” is employed for workpiece image acquisition, geometric feature analysis, and color recognition. I/O communication is utilized to establish signal transmission between the vision module and the mechanical arm. Based on machine vision recognition outcomes, the mechanical arm systematically stores workpieces in accordance with predefined rules. The vision module leverages graphic geometric features, the Vision Master algorithm for workpiece identification, classification, and the acquisition of pertinent pose parameters. Additionally, the vision module incorporates a circular light source, ensuring adaptability to diverse lighting conditions for recognition and detection. Through communication and data exchange between the machine vision module and a 6-axis mechanical arm, this design successfully accomplishes workpiece recognition and automated sorting in warehousing, yielding highly satisfactory results.