Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki

Zubčić, Matej

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master's thesis

Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki

2017. urn:nbn:hr:200:613607

Zubčić, Matej

Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Computer Engineering

Cite this document

APA 6th Edition

Zubčić, M. (2017). Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:613607

MLA 8th Edition

Zubčić, Matej. "Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2017. https://urn.nsk.hr/urn:nbn:hr:200:613607

Chicago 17th Edition

Harvard

Zubčić, M. (2017). 'Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 23 April 2024, https://urn.nsk.hr/urn:nbn:hr:200:613607

Vancouver

Zubčić M. Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2017 [cited 2024 April 23] Available at: https://urn.nsk.hr/urn:nbn:hr:200:613607

IEEE

M. Zubčić, "Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:200:613607

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:613607

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Title	Određivanje položaja objekta u prostoru na temelju sinergije višesenzorskih prostorno vremenskih značajki
Title (english)	The positioning of the object in space based on the synergy of multisensor spatio-temporal features
Author	Matej Zubčić
Mentor	Tomislav Keser (mentor)
Committee member	Tomislav Keser (predsjednik povjerenstva)
Committee member	Alfonzo Baumgartner (član povjerenstva)
Committee member	Krešimir Nenadić (član povjerenstva)
Granter	Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering, Computer Science and Information Technology Osijek (Department of Computer Engineering and Automation) (Chair of Computer Engineering) Osijek
Defense date and country	2017-10-05, Croatia
Scientific / art field, discipline and subdiscipline	TECHNICAL SCIENCES Computing Process Computing
Abstract	U ovome radu objašnjen je problem određivanja položaja na temelju vektorskih mjerenja senzora. S obzirom na problematiku korištenih senzora pri određivanju položaja, kao estimator položaja izabran je multiplikativni prošireni Kalmanov filter zbog svojih prednosti. Prednosti ovog filtera su računska jednostavnost s obzirom kako su jednadžbe filtera razvijene na temelju kvaternionske parametrizacije položaja. Dodatna prednost ovog filtera je i ta, da filter ne estimira dinamiku stanja tijela, nego samo stanje pogrešaka položaja koje se dodaju na nominalno stanje sustava, a to dodatno ubrzava iteraciju algoritma. Rezultat ovog rada je uspješna implementacija MEKF algoritma u Matlabu, što je i potvrđeno kroz pokuse i mjerenja s obzirom na referentne skupove mjerenja. Rad daje i objašnjenje problema prilikom korištenja izabranog referentnog skupa mjerenja.
Abstract (english)	This thesis explains attitude determination problem based on sensor measurements in vector space. It gives a short overview of deterministic methods used to solve this problem and then progresses with the state space stochastic methods, mainly using the Multiplicative Extended Kalman Filter. The MEKF was chosen due to its advantages, which include, lower computational requirements since state equations are developed using quaternion parametrization of attitude, hence there is no trigonometric operations used in the state transition equation. One additional advantage of this filter is its complementary or indirect nature, i.e. we are not estimating the full-state of the system, just the error-states which brings additional simplifications and robustness when using MEKF for attitude estimation. The result of this work is a successful implementation of the MEKF algorithm in a discrete form, using Matlab, this form is suitable for calculation on digital computers or embedded systems. Implementation is evaluated through comparison of attitude estimates with highly accurate reference measurements. Unfortunately, due to a mistake in the experiments when the reference measurements were gathered, it wasn’t possible to correctly evaluate accuracy of the estimated yaw angle.
Keywords
Keywords (english)
Language	croatian
URN:NBN	urn:nbn:hr:200:613607
Study programme	Title: Graduate University Study Programme in Computer Engineering Study programme type: university Study level: graduate Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resource	Text
File origin	Born digital
Access conditions	Open access
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Created on	2018-05-28 10:54:40