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undergraduate thesis
Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:154177
Sorić, Petar
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Sorić, P. (2022). Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:154177

Sorić, Petar. "Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:154177

Sorić, Petar. "Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:154177

Sorić, P. (2022). 'Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:154177

Sorić P. Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 July 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:154177

P. Sorić, "Upravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:154177

Metadata
TitleUpravljanje SofIA robotskom hvataljkom temeljeno na dubokim neuronskim mrežama
Title (english)Deep learning based control of robotic gripper SofIA
AuthorPetar Sorić
MentorMatko Orsag (mentor)
Committee memberMatko Orsag (član povjerenstva)
Committee memberJelena Vuletić (član povjerenstva)
Committee memberRobert Milijaš (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu opisan je postupak razvoja jedne konvolucijske neuronske mreže koja uspješno klasificira slike pribavljene sa robotske hvataljke SofIA. Napravljen je pregled nekoliko radova iz područja "soft" robotike koji se bave sličnom tematikom. Opisani su koraci generiranja sintetskih podataka za treniranje u programu Blender i prikazana je struktura tih podataka. U daljnjim poglavljima opisana je struktura konvolucijske neuronske mreže i njena programska implementacija. Neuronska mreža trenirana je koristeći 3 različite kombinacije sintetskih i pravih podataka za treniranje, za svaku kombinaciju testirali smo neuronsku mrežu na pravim podacima. Odabrali smo najbolje rješenje koje ima približno 95% točnosti na pravim podacima. Usporedili smo ostala rješenja s najboljim i komentirali rezultate.
Abstract (english)
This paper describes the development of a convolutional neural network used for classification of pictures obtained from SofIA robotic gripper. A brief overview of the soft robotics research area is written, commenting on a few papers researching soft robotic grippers. The process of generating the synthethic dataset in Blender and it's structure is described in detail in the next chapter. After generating the dataset used for training the neural network, the structure and specific parameters of the network is described. The code and other tools used for designing, training and testing the neural network is shown next. There were 3 different training methods used, a combination of synthethic and real data. The best of the three approaches was picked as the final solution, which had a 95% accuracy when tested on a real sample.Finally, the three approaches were compared based on their accuracy and the results were discussed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:154177
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-01-15 11:14:28