prikaz prve stranice dokumenta High-dimensional trajectory optimization for robot motion planning based on Gaussian processes
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doctoral thesis
High-dimensional trajectory optimization for robot motion planning based on Gaussian processes
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:262919
Petrović, Luka
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Control and Computer Engineering

Institutional repository: FER Repository

Cite this document

Petrović, L. (2022). High-dimensional trajectory optimization for robot motion planning based on Gaussian processes (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:262919

Petrović, Luka. "High-dimensional trajectory optimization for robot motion planning based on Gaussian processes." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:262919

Petrović, Luka. "High-dimensional trajectory optimization for robot motion planning based on Gaussian processes." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:262919

Petrović, L. (2022). 'High-dimensional trajectory optimization for robot motion planning based on Gaussian processes', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:262919

Petrović L. High-dimensional trajectory optimization for robot motion planning based on Gaussian processes [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:262919

L. Petrović, "High-dimensional trajectory optimization for robot motion planning based on Gaussian processes", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:262919

Metadata
TitleHigh-dimensional trajectory optimization for robot motion planning based on Gaussian processes
Title (croatian)Optimizacija visokodimenzijskih trajektorija za planiranje gibanja robota zasnovana na Gaussovim procesima
AuthorLuka Petrović
MentorIvan Marković (mentor)
Committee memberStjepan Bogdan (predsjednik povjerenstva)
Committee memberMarija Seder (član povjerenstva)
Committee memberMarko Švaco (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Control and Computer Engineering)
Zagreb
Defense date and country2022-07-18, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Motion planning is one of the fundamental tasks in robotics with the goal of producing feasible robot trajectories in configuration space that reach a desired goal optimally according to a given criterion. The principal purpose of this thesis is the development of novel high-dimensional motion planning methods that enable safe and efficient robot operation in real-world environments. We rely on trajectory optimization in order to produce robot trajectories that are smooth, collision-free and satisfy arbitrary task-dependent criteria. A common theme throughout this thesis is reliance on continuous-time Gaussian processes as trajectory representations that underpin efficient collision-checking and generate smooth robot trajectories. The thesis presents three scientific contributions: 1 A method for stochastic high-dimensional robot trajectory optimization based on cross-entropy and heteroscedastic Gaussian processes. 2 A high-dimensional trajectory optimization method based on stochastic gradient estimation using mixtures of Gaussian processes that enables inclusion of multiple complex criteria. 3 An incremental factor graph inference method for simultaneous moving object tracking and robot motion planning based on Gaussian processes.
Abstract (croatian)
Planiranje gibanja predstavlja jedan od temeljnih problema u robotici s ciljem generiranja ostvarivih robotskih trajektorija koje uspješno izvršavaju dani zadatak. Temeljni je cilj ove disertacije razvoj novih visokodimenzijskih algoritama planiranja gibanja koji omogućuju sigurno i učinkovito djelovanje robota u stvarnim, dinamičkim okruženjima. U radu se oslanjamo na metode optimizacije trajektorija kako bismo generirali glatke putanje robota koje nisu u sudaru s okolinom i zadovoljavaju proizvoljne optimizacijske kriterije. Oslanjamo se i na kontinuirane Gaussove procese za predstavljanje trajektorije čime je omogućena efikasna provjera sudara i postizanje visoke brzine izvođenja navedenih metoda. Tri su znanstvena doprinosa disertacije: 1 Metoda za stohastičku optimizaciju visokodimenzijske trajektorije robota zasnovana na unakrsnoj entropiji i heteroskedastičnim Gaussovim procesima. 2 Metoda optimizacije visokodimenzijskih trajektorija zasnovana na stohastičkoj estimaciji gradijenta korištenjem mješavine Gaussovih procesa koja omogućuje uključivanje više složenih kriterija. 3 Inkrementalna metoda zaključivanja na faktor grafu za istovremeno praćenje gibajućih objekata i planiranje gibanja robota zasnovana na Gaussovim procesima.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:168:262919
Promotion2022
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Type of resourceText
Extentxvi, 135 str. : ilustr. u boji ; 30 cm.
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2022-09-12 08:22:07