In production, we are striving for the highest reliability and repeatability of all processes, thus achieving as little congestion as possible and thus reducing wastes. One of the basic processes in the automated line within Industry 4.0 is the stacking, sorting and separation of various products and components, mainly due to the striving for mixed lines where we want to produce more products on one line. To carry out such a process, robots are used in combination with machine vision and suitable algorithms for process control.
The purpose of this diploma is to develop an algorithm that will recognize randomly shaped shapes and colors in the robot working space, and put them in a predetermined place.
To test the algorithm we used a test station with a fixed USB digital camera, for position and color capture, and an uArm robot for manipulating pieces. The test station simulates the standing conveyor belt, in which different colors randomly oriented pieces come to the robot. The camera captures the image, and analyzed it with the developed algorithm to obtain information on the color, orientation and position of individual pieces. The data is then sent to the robot to collect items and fold them in a predetermined position.
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