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undergraduate thesis
Evolucijsko optimiranje neuronske mreže mobilnog robota
Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2022. urn:nbn:hr:235:718120
Dragičević, Nino
University of Zagreb
Faculty of Mechanical Engineering and Naval Architecture

Institutional repository: Repository of Faculty of Mechanical Engineering and Naval Architecture University of Zagreb

Cite this document

Dragičević, N. (2022). Evolucijsko optimiranje neuronske mreže mobilnog robota (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture. Retrieved from https://urn.nsk.hr/urn:nbn:hr:235:718120

Dragičević, Nino. "Evolucijsko optimiranje neuronske mreže mobilnog robota." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:235:718120

Dragičević, Nino. "Evolucijsko optimiranje neuronske mreže mobilnog robota." Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, 2022. https://urn.nsk.hr/urn:nbn:hr:235:718120

Dragičević, N. (2022). 'Evolucijsko optimiranje neuronske mreže mobilnog robota', Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, accessed 30 June 2024, https://urn.nsk.hr/urn:nbn:hr:235:718120

Dragičević N. Evolucijsko optimiranje neuronske mreže mobilnog robota [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture; 2022 [cited 2024 June 30] Available at: https://urn.nsk.hr/urn:nbn:hr:235:718120

N. Dragičević, "Evolucijsko optimiranje neuronske mreže mobilnog robota", Undergraduate thesis, University of Zagreb, Faculty of Mechanical Engineering and Naval Architecture, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:235:718120

Metadata
TitleEvolucijsko optimiranje neuronske mreže mobilnog robota
Title (english)Evolutionary optimization of mobile robot neural network
AuthorNino Dragičević
MentorPetar Ćurković (mentor)
Committee memberMiro Hegedić (predsjednik povjerenstva)
Committee memberPetar Ćurković (član povjerenstva)
Committee memberTihomir Opetuk (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mechanical Engineering and Naval Architecture
Zagreb
Defense date and country2022-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
Razvoj umjetne inteligencije omogućava otkrivanje novih metoda za rješavanje dosadašnjih optimizacijskih problema. Primjena evolucijskih mehanizama u razvoju novih rješenja za razne probleme optimizacije oduvijek je bila zanimljiva tema kojom se bave i robotika i računarstvo. Cilj rada bio je pobliže proučiti područje evolucijske robotike te implementirati evolucijski algoritam koji optimira rad neuronske mreže u virtualnom okruženju na problemima praćenja ravne linije i slijeđenja izvora svjetlosti. Ovaj rad ispitao je kako se evolucijskim algoritmom evoluira neuronska mreža, koja služi za upravljanje Braitenbergovog modela mobilnog robota. Objašnjeni su glavni mehanizmi evolucije i princip rada neuronskih mreža. Izvršena je implementacija pomoću Neuro Evolution of Augmenting Topologies (NEAT) algoritma u programskom jeziku python, koji je korišten za rješavanje problema slijeđenja ravne linije i praćenja izvora svjetlosti.
Abstract (english)
The development of artificial intelligence enables the discovery of new methods for solving existing problems. The application of evolutionary mechanisms in the development of new solutions to various problems has always been an interesting topic to both robotics and computer science. The aim of this study was to examine the field of evolutionary robotics in more detail, and to implement an evolutionary algorithm that optimizes the operation of a neural network in a virtual environment on the problems of tracking a straight line, and following a light source. This study investigated how the evolutionary algorithm evolves a neural network which is used to control Braitenberg's model of a mobile robot. The main mechanisms of evolution and the working principle of neural networks were explained. Implementation was performed using the Neuro Evolution of Augmenting Topologies (NEAT) algorithm in the python programming language which was used to solve the problems of following a straight line and tracking a light source.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:235:718120
Study programmeTitle: Mechanical Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka strojarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-09-23 15:10:52