iCIM – Integration of Mitsubishi RV-6S Industrial Robot and Machine Vision System
Erkkilä, Tuomas (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025052013744
https://urn.fi/URN:NBN:fi:amk-2025052013744
Tiivistelmä
This thesis presents the design and implementation of an autonomous robotic work cell capable of identifying, classifying, and handling small components using machine vision. The system integrates a Mitsubishi RV-6S industrial robot, a dual-mode gripper, and a machine vision solution powered by MVTec HALCON.
The machine vision system was developed to distinguish object types and holster configurations through custom image analysis. Gripping functionality combined mechanical and vacuum methods, supported by a 3D-printed holster that enabled flexibility and durability in component handling. Control architecture centred around a Siemens SIMATIC ET200SP logic module, coordinated by a PLC and I/O communication.
The robotic system reliably processed various objects – including copper and aluminium cylinders, thermometers, and hygrometers – under varying lighting and positional conditions. While full integration between robot and vision subsystems was not finalized, the modular design enables future upgrades and scalability.
The results demonstrate that a vision-guided, dual-gripping robotic cell with structured I/O integration can improve efficiency and adaptability in industrial part classification tasks.
The machine vision system was developed to distinguish object types and holster configurations through custom image analysis. Gripping functionality combined mechanical and vacuum methods, supported by a 3D-printed holster that enabled flexibility and durability in component handling. Control architecture centred around a Siemens SIMATIC ET200SP logic module, coordinated by a PLC and I/O communication.
The robotic system reliably processed various objects – including copper and aluminium cylinders, thermometers, and hygrometers – under varying lighting and positional conditions. While full integration between robot and vision subsystems was not finalized, the modular design enables future upgrades and scalability.
The results demonstrate that a vision-guided, dual-gripping robotic cell with structured I/O integration can improve efficiency and adaptability in industrial part classification tasks.