The final thesis deals with the topic of automated collection of bulk products. The problem, whose solutions are presented during the task, is to recognize the position and orientation of objects randomly distributed in space. The first part of the thesis gives an overview of the current state of the art in the field of product picking and three-dimensional scanners and summarizes the theoretical background of some of the functions for the identification of products. In the second part of the thesis a 3D scanner was used to capture 3D images of bulk objects. This was followed by the development of a software in the programming language Python, with which we processed the 3D images and converted them into images with depth of field. Later, we have further processed these images with various functions available within open source libraries, which we then used as input in three different functions to identify simple objects. At the end of the assignment, we checked the results of each function on different sets of stage images showing objects with different shapes. Based on the results, we evaluated each function and estimated whether it was suitable for identifying bulk products.
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