{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T03:46:25Z","timestamp":1766720785416,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006141","name":"Wojskowa Akademia Techniczna","doi-asserted-by":"publisher","award":["UGB 22-856"],"award-info":[{"award-number":["UGB 22-856"]}],"id":[{"id":"10.13039\/501100006141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper presents a solution to the problem of simultaneous localization and mapping (SLAM), developed from a particle filter, utilizing a monocular camera as its main sensor. It implements a novel sample-weighting idea, based on the of sorting of particles into sets and separating those sets with an importance-factor offset. The grouping criteria for samples is the number of landmarks correctly matched by a given particle. This results in the stratification of samples and amplifies weighted differences. The proposed system is designed for a UAV, navigating outdoors, with a downward-pointed camera. To evaluate the proposed method, it is compared with different samples-weighting approaches, using simulated and real-world data. The conducted experiments show that the developed SLAM solution is more accurate and robust than other particle-filter methods, as it allows the employment of a smaller number of particles, lowering the overall computational complexity.<\/jats:p>","DOI":"10.3390\/rs13163233","type":"journal-article","created":{"date-parts":[[2021,8,15]],"date-time":"2021-08-15T22:51:27Z","timestamp":1629067887000},"page":"3233","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Stratified Particle Filter Monocular SLAM"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7299-9579","authenticated-orcid":false,"given":"Pawel","family":"Slowak","sequence":"first","affiliation":[{"name":"Faculty of Electronics, Military University of Technology, ul. gen. S. Kaliskiego 2, 00-908 Warsaw, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3873-2894","authenticated-orcid":false,"given":"Piotr","family":"Kaniewski","sequence":"additional","affiliation":[{"name":"Faculty of Electronics, Military University of Technology, ul. gen. S. Kaliskiego 2, 00-908 Warsaw, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1109\/TRO.2016.2624754","article-title":"Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age","volume":"32","author":"Cadena","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.robot.2017.09.010","article-title":"Keyframe-based monocular SLAM: Design, survey, and future directions","volume":"98","author":"Younes","year":"2017","journal-title":"Rob. Auton. 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