ABSTRACT
In 2020, the global educational models became fully modified, migrating to a remote modality due to the global COVID-19 pandemic. This presented a massive challenge for educational programs with high technical content. In specific areas such as industrial process automation, new teaching models were adapted to lead the student to efficient learning through automated system simulators in the industrial area. This project aimed to design and develop a redundant robotic system with 7 degrees of freedom and computational vision. We used computer simulators to improve students' learning experience in technical industrial-process-automation classes. To achieve the control and programming of the redundant robot, we used the CoppeliaSim robotic simulator (V-REP), which allows creating, composing, and simulating almost any type of robot with precise physical motors. This simulator facilitates coding robots with the Python programming language. The OpenCV library was also utilized to integrate a computer vision system into the simulator. An automated (simulated) object classification system was designed using a redundant seven-degrees-of-freedom (7DOF) robot and a computational vision system. The vision system was designed to identify and classify PCB electronic boards with a barcode. The simulator allowed users to learn Python to program the robot's movements to fulfill a specific task. Additionally, it allowed users to learn to develop computer programs incorporating computational vision to monitor industrial processes.