Назва:
The Probabilistic Approach to Automated Visual Navigation in Closed Spaces

dc.contributor.authorArtemenko, Olga
dc.contributor.authorDorenskyi, Oleksandr
dc.contributor.authorTerletskyi, Taras
dc.contributor.authorKaidyk, Oleh
dc.contributor.authorKramar, Oleh
dc.date.accessioned2026-06-23T10:57:12Z
dc.date.issued2026-02-07
dc.description.abstractThe paper reviews current approaches to automated navigation tasks, such as localization and mapping, and proposes a different approach based on probability density approximation. The proposed system uses feature extraction to reduce computation complexity. Descriptors, are then used to match mapped features to a current view, and localization uses iterative pose estimation based on gradient descent. Current system limitations and weaknesses are also shown
dc.identifier.citationArtemenko O., Dorenskyi O., Terletskyi T., Kaidyk O., Kramar A. The probabilistic approach to automated visual navigation in closed spaces. CEUR Workshop Proceedings: Applied Information Technologies and Artificial Intelligence Systems (AIT&AIS 2025). 2026. № 4160. 319–331. https://ceur-ws.org/Vol-4160/paper19.pdf
dc.identifier.issn1613-0073
dc.identifier.urihttps://repository.lntu.edu.ua/handle/123456789/4906
dc.language.isoen
dc.subjectvisual odometry
dc.subjectmapping
dc.subjectlocalization
dc.subjectfeature extraction
dc.subjectprobability density approximation
dc.titleThe Probabilistic Approach to Automated Visual Navigation in Closed Spaces
dc.typeArticle
dspace.entity.typeScientificArticle

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