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master's thesis
Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:173299
Vuksanović, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Vuksanović, F. (2021). Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:173299

Vuksanović, Filip. "Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:173299

Vuksanović, Filip. "Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:173299

Vuksanović, F. (2021). 'Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:173299

Vuksanović F. Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:173299

F. Vuksanović, "Semantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:173299

Metadata
TitleSemantička segmentacija rupa na cesti za autonomni vizualni pregled bespilotnom letjelicom
Title (english)Semantic segmentation of road potholes for autonomous visual inspection with unmanned aerial vehicle
AuthorFilip Vuksanović
MentorStjepan Bogdan (mentor)
Committee memberStjepan Bogdan (predsjednik povjerenstva)
Committee memberZdenko Kovačić (član povjerenstva)
Committee memberGoran Vasiljević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Abstract
Bespilotne letjelice se posljednjih godina sve više koriste u svrhu inspekcije različitih infrastruktura. Ceste su jedan od primjera infrastrukture kojem je potreban redoviti pregled jer se svakodnevno pojavljuju nova oštećenja na cestama. Trenutne metode vremenski drugo traju i skupocjene su jer su ljudi ti koji izvršavaju pregled. Kako bi se riješio taj problem, u ovom diplomskom radu je predložena metoda cestovnih pregleda u kojoj se koriste podaci sa stereo kamere i senzora postavljenih na bespilotnoj letjelici. Prvo se pomoću segmentacije instanci, za koju se koristi model neuronski mreža poznat kao Mask R-CNN, otkrivaju rupe na cesti. Zatim se pozicija rupa u globalnom koordinatnom sustavu izračunava na temelju senzorskih očitanja s letjelice i pozicije letjelice u prostoru. Na kraju se očitani rezultati grupiraju aglomerativnom metodom grupiranja te se za svaku grupu računa centroid koji predstavlja poziciju rupe u globalnom sustavu. Predložena metoda je testirana u Gazebo simulatoru s letjelicom koja na sebi ima stereo kameru. Eksperimentalni rezultati su pokazali kako se korištenjem ove metode mogu detektirati rupe te izračunati njihove pozicije u globalnom koordinatnom sustavu.
Abstract (english)
Unmanned aerial vehicles (UAVs) have been widely used for infrastructure inspections in recent years. Roads are one of those infrastructures that need constant inspection as there are new road damages every day. Current methods of road inspections are time-consuming and costly as they are usually inspected manually. To address this problem, this thesis proposes a process for pothole inspection based on stereo camera and UAV’s inertial measurement units (IMUs) sensors. First, the instance segmentation method based on Mask R-CNN was used for pothole detection. Then, the positions of the potholes were calculated based on the UAV’s IMUu sensors and the position of the UAV in the global coordinate system. Finally, the agglomerative clustering method was used to cluster the calculated potholes’ positions. The centroid of each cluster represents the pothole’s coordinate in the global coordinate system. The proposed process was implemented in the Gazebo simulator, in which the UAV model has a mounted stereo camera. The experimental results show that this process is capable of detecting potholes and calculating the potholes’ coordinates.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:173299
Study programmeTitle: Electrical Engineering and Information Technology
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije (magistar/magistra inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
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Created on2023-01-13 14:16:54