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 imp
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