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Prepoznava izdelkov v razsutem stanju
ID Arko, Gregor (Author), ID Bračun, Drago (Mentor) More about this mentor... This link opens in a new window

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Abstract
Diplomska naloga obravnava tematiko avtomatiziranega pobiranja izdelkov v razsutem stanju. Problem, katerega rešitve so predstavljene tekom naloge, je prepoznava lege in orientacije objektov, ki so naključno razporejeni v prostoru. V prvem delu naloge je opravljen pregled obstoječega stanja tehnike na področju pobiranja izdelkov in tridimenzionalnih merilnikov ter povzeto teoretično ozadje nekaterih uporabljenih funkcij za prepoznavo izdelkov. V drugem delu diplomske naloge smo uporabili 3D merilnik za zajem 3D slik objektov v razsutem stanju. Sledil je razvoj programske opreme v programskem jeziku Python, s katero smo nato obdelali 3D slike in jih pretvorili v intenzitetne globinske slike. V nadaljevanju smo te slike še dodatno obdelali z različnimi funkcijami, ki so dostopne znotraj odprtokodnih knjižnic ter jih nato uporabili kot vhodne podatke v treh različnih funkcijah za prepoznavo enostavnih objektov. V zaključku naloge smo preverili delovanje posamezne funkcije na različnih scenskih slikah, na katerih so bili objekti različnih oblik. Na podlagi rezultatov smo ovrednotili posamezno funkcijo ter ocenili, ali je primerna za prepoznavo izdelkov v razsutem stanju.

Language:Slovenian
Keywords:prepoznava objektov, lega v prostoru, 3D slike, obdelava slik, avtomatizacija
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FS - Faculty of Mechanical Engineering
Place of publishing:Ljubljana
Publisher:[G. Arko]
Year:2020
Number of pages:XXII, 58 str.
PID:20.500.12556/RUL-116047 This link opens in a new window
UDC:004.932.72:681.5(043.2)
COBISS.SI-ID:16655875 This link opens in a new window
Publication date in RUL:09.05.2020
Views:814
Downloads:185
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Secondary language

Language:English
Title:Recognition of bulk products
Abstract:
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.

Keywords:objects identification, position in space, 3D images, images processing, automatization

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