System for Automatic Calibration of a Robotic Tool

This Master's thesis describes the design and implementation of an experimental sample for automatic calibration of a robotic tool using machine vision methods under the auspices of the company SANEZOO EUROPE s.r.o. It deals with the analysis of all used methods of performing TCP calibration, on the basis of which it is implemented. The application is based on the Point-counterpoint method, where the robot is guided against the calibration point from three different directions, all perpendicular to each other. The calibration point is set using the ArUco marker. In order to detect the endpoint are used images from two cameras that are at the right angles to each other. Using conventional computer vision methods and an HSV filter, the endpoint of the instrument is found in the images and is guided to the calibration point. From the obtained coordinates, the searched endpoint of the robotic tool in the robot coordinates is found using the optimization method Particle Swarm Optimization. This application, therefore, performs TCP calibration in a fast time, thus reducing production downtime almost without human intervention