Despite advances in teaching methods and the inclusion of contemporary tools in the learning process, the success rate is low. It is sought to add in their educational training, theory and practice for the student, learning, new knowledge, and skills within their training as an engineer.
This article presents a methodology to improve the performance of learning of students in the major of Automation Engineering, through the development of a multidisciplinary project that involves the use of contemporary technological tools and knowledge of previous subjects. It performs an excellent size and shapes recognition precision in real-time with 100% accuracy. Empirical results demonstrate that the designed robotic arm detects colored objects with 80% accuracy. The proposed system can also detect objects' geometrical shapes (circle, triangle, square, rectangle, pentagon, and star) and sizes (large, medium, and small) by utilizing OpenCV image processing libraries in Python language. Finally, the device releases the object according to its color behind the fixed positions of the robotic arm to a specific place.
Next, a preprogrammed command is generated in the robotic arm to pick the item employing Arduino Mega and four MG996R servo motors. This study utilizes the image processing methodology of the Pix圜MU camera sensor to distinguish multiple objects according to their distinct colors (red, yellow, and green). In this paper, an automatic computer vision-based robotic gripper has been built that can select and arrange objects to complete various tasks. As a result of this blessing of technological advances, robots will perform jobs far more efficiently than humans in challenging situations. With time, electronic technology has advanced, and the ultimate goal of such technological advances is to make robotic systems as human-like as possible. Nowadays, industrial activities have become more automated, increasing efficiency while reducing the production time, human labor, and risks involved. Various aspects of the human workplace have been influenced by robotics due to its precision and accessibility.
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