Назва: The Probabilistic Approach to Automated Visual Navigation in Closed Spaces
| dc.contributor.author | Artemenko, Olga | |
| dc.contributor.author | Dorenskyi, Oleksandr | |
| dc.contributor.author | Terletskyi, Taras | |
| dc.contributor.author | Kaidyk, Oleh | |
| dc.contributor.author | Kramar, Oleh | |
| dc.date.accessioned | 2026-06-23T10:57:12Z | |
| dc.date.issued | 2026-02-07 | |
| dc.description.abstract | The 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.citation | Artemenko 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.issn | 1613-0073 | |
| dc.identifier.uri | https://repository.lntu.edu.ua/handle/123456789/4906 | |
| dc.language.iso | en | |
| dc.subject | visual odometry | |
| dc.subject | mapping | |
| dc.subject | localization | |
| dc.subject | feature extraction | |
| dc.subject | probability density approximation | |
| dc.title | The Probabilistic Approach to Automated Visual Navigation in Closed Spaces | |
| dc.type | Article | |
| dspace.entity.type | ScientificArticle |
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