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master's thesis
Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:160765
Jukić, Ana Petra
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Jukić, A. P. (2023). Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:160765

Jukić, Ana Petra. "Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:160765

Jukić, Ana Petra. "Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:160765

Jukić, A. P. (2023). 'Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 12 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:160765

Jukić AP. Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 July 12] Available at: https://urn.nsk.hr/urn:nbn:hr:168:160765

A. P. Jukić, "Autonomno upravljanje vozilom zasnovano na metodama dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:160765

Metadata
TitleAutonomno upravljanje vozilom zasnovano na metodama dubokog učenja
Title (english)Autonomous vehicle control based on deep learning methods
AuthorAna Petra Jukić
MentorMarija Seder (mentor)
Committee memberIvan Marković (član povjerenstva)
Committee memberJuraj Peršić (član povjerenstva)
Committee memberLuka Petrović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-11, Croatia
Abstract
Tradicionalni sustavi autonomne vožnje sastoje se od percepcije, lokalizacije, mapiranja, planiranja i praćenja putanje, gdje svaki korak može biti vrlo računski zahtjevan pogotovo u kompleksnim i dinamičkim okruženjima. U diplomskom je radu potrebno ostvariti autonomnu vožnju automobila korištenjem dubokih modela, poput konvolucijskih neuronskih mreža koji će na temelju senzorskih podataka (iz kamere, lasera i radara) izravno odrediti upravljačke naredbe. Evaluaciju modela je potrebno napraviti u simulatoru tako da automobil tijekom vožnje uvijek ostane na stazi pri različitim vremenskim uvjetima i uvjetima osvjetljenja.
Abstract (english)
Traditional autonomous driving systems consist of perception, localization, mapping, planning and trajectory tracking, where each step can be very computationally demanding, especially in complex and dynamic environments. In the thesis, it is necessary to achieve autonomous car driving using deep models, such as convolutional neural networks, which will directly determine control commands based on sensor data (from cameras, lasers and radars). The evaluation of the model must be done in the simulator so that the car always stays on the track while driving under different weather and lighting conditions.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:160765
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-10-11 09:10:35