Augmented reality for teaching high-precision robot movements

V industriji zadnja leta vse bolj težijo k čim bolj optimiziranim procesom in s tem višji produktivnosti. Sodelujoči roboti so eni izmed tehnoloških napredkov v zadnjem času, ki veliko pripomore k industriji 4.0, saj lahko v različnih procesih pomagajo človeku, brez da bi ta bil ogrožen. V magistrski nalogi smo želeli preizkusiti sodelovanje človeka in robota pri zajemu vzorca bakterijskih kolonij. Naredili smo celoten sistem, ki je bil primeren za tako aplikacijo, vključno z vsemi programskimi rešitvami, ki so potrebne za tako natančno vodenje robota. Robotski sistem in vsa ostala strojna oprema je komunicirala med sabo, da je delo za operaterja potekalo nemoteno. Samo virtualno okolje je bilo prilagojeno laboratorijskemu okolju, kjer se v večini primerov tudi opravlja zajem vzorcev. Problematika projekta je bila v prvi vrsti natančnost robota in kalibracija orodji na vrhu robota, ki smo jih uporabljali. Na rezultatih pa se opazi tudi probleme pri različnih načinih vizualizacije, kje operater ni še preveč suveren oziroma premalo izučen. Glede na rezultate lahko sklepamo, da se ponovljivost zajema s povečavo in 3D prikazom nekajkrat izboljša. Ob tem se hitrost zajema in gladkost trajektorije zmanjšata, ampak z dodatnim treningom in nadaljnjim razvojem aplikacije ter sistema bi lahko izboljšali rezultate.The industry has increasingly strived to optimise processes and increase productivity in recent years. Collaborative robots are one of the recent technological advances which significantly contribute to Industry 4.0, as they can be used in various processes without putting humans at risk. In this master thesis, we evaluated human-robot collaboration to pick a bacterial colony sample. We developed a complete robot system suitable for such an application, including the software solutions needed to control the robot with the required precision. The robot system communicated with other hardware so that the operator could perform work smoothly. The virtual environment itself was an adapted laboratory environment, where most of the bacterial sample collection is carried out. The main issues encountered during the research were primarily robot accuracy and calibration of the tools at the robot end-effector. However, the results also show differences with the different visualisation modes, where the operator is not yet very proficient or not skilled enough. From the results, we can conclude that the repeatability of the bacterial colony picking is increased with magnification and 3D display. At the same time, the picking speed and the smoothness of the trajectory are reduced. With additional training and further development of the application, the results can be im