20.500.12556/DKUM-93583 Analiza vpliva senzorske tehnologije na zanesljivost delovanja mobilnega robota v zahtevnih okoljih magistrsko delo Analysis of sensor integration effects on mobile robot operational performance in adverse environments V magistrski nalogi obravnavamo uporabo avtonomnih mobilnih robotov v kontekstu Industrije 4.0, s poudarkom na izzivih lokalizacije in navigacije v kompleksnih industrijskih okoljih. Tradicionalne metode, ki temeljijo na posameznih senzorskih virih, se pogosto izkažejo za nezanesljive, zato raziskava analizira uporabo multisenzorske fuzije, ki združuje podatke iz LiDAR, IMU in RGB kamer. Osrednji del predstavlja analizo učinkovitosti različnih navigacijskih algoritmov, med katerimi izstopajo EKF, SLAM, DWA in RRT*. Predstavimo tudi simulacijski pristop z uporabo orodij, kot sta MATLAB/Simulink in Gazebo. V ospredju je optimizacija poti, robustnost sistema, odzivnost na okoljske spremembe in zmanjševanje energetske porabe. Ugotovljeno je, da kombinacija senzorjev in naprednih algoritmov vodi do bistveno večje natančnosti in operativne zanesljivosti. Ekonomskega pomena raziskave ni mogoče zanemariti, saj uspešna uvedba AMR tehnologij omogoča zmanjšanje stroškov dela, povečanje produktivnosti in fleksibilno reorganizacijo proizvodnih procesov. Zaključki predstavljajo temelj za nadaljnji razvoj pametnih tovarn, pri čemer je ključna integracija tehničnih in ekonomskih vidikov. In this master’s thesis, we examine the use of autonomous mobile robots (AMRs) in the context of Industry 4.0, with the focus on the challenges of localization and navigation in complex industrial environments. Traditional methods based on individual sensor sources often prove to be unreliable; therefore, the research analyzes the application of multisensor fusion, which combines data from LiDAR, IMU, and RGB cameras. The core of the study is the analysis of the efficiency of various navigation algorithms, among which EKF, SLAM, DWA, and RRT* stand out. We also present a simulation-based approach using tools such as MATLAB/Simulink and Gazebo. The focus is on path optimization, system robustness, responsiveness to environmental changes, and reduction of energy consumption. It is found out that the combination of sensors and advanced algorithms leads to significantly higher accuracy and operational reliability. The economic relevance of the research should not be overlooked, as the successful implementation of AMR technologies enables labor cost reduction, increased productivity, and flexible reorganization of production processes. The conclusions serve as a foundation for the further development of smart factories, where the integration of technical and economic aspects is essential. robot senzor navigacija okolje lokalizacija robot sensor navigation environment localization true true false [M. Jarnovič] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2025-07-03 12:06:40 2025-08-20 12:59:30 2025-09-13 03:27:22 0000-00-00 00:00:00 2025 0 Maribor 0 Maribor 1 spletni vir (1 datoteka PDF (XI, 60 f.)) 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 007.52(043.2) 248707587 MAG_Jarnovic_Maksim_2025.pdf MAG_Jarnovic_Maksim_2025.pdf 1 461BE0507016FA89026EE0436589F2E2 ab78b592a96b8e93a99176b60a6d0a98570bb0af080eb8c9b2d508012c129905 a91a57f2-5800-11f0-95d1-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=193223 Fakulteta za strojništvo 0 0 0