{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T18:40:36Z","timestamp":1764873636624,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["DPI2017-85007-R"],"award-info":[{"award-number":["DPI2017-85007-R"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Keeping a vehicle well-localized within a prebuilt-map is at the core of any autonomous vehicle navigation system. In this work, we show that both standard SIR sampling and rejection-based optimal sampling are suitable for efficient (10 to 20 ms) real-time pose tracking without feature detection that is using raw point clouds from a 3D LiDAR. Motivated by the large amount of information captured by these sensors, we perform a systematic statistical analysis of how many points are actually required to reach an optimal ratio between efficiency and positioning accuracy. Furthermore, initialization from adverse conditions, e.g., poor GPS signal in urban canyons, we also identify the optimal particle filter settings required to ensure convergence. Our findings include that a decimation factor between 100 and 200 on incoming point clouds provides a large savings in computational cost with a negligible loss in localization accuracy for a VLP-16 scanner. Furthermore, an initial density of \u223c2 particles\/m     2     is required to achieve 100% convergence success for large-scale (\u223c100,000 m     2    ), outdoor global localization without any additional hint from GPS or magnetic field sensors. All implementations have been released as open-source software.<\/jats:p>","DOI":"10.3390\/s19143155","type":"journal-article","created":{"date-parts":[[2019,7,18]],"date-time":"2019-07-18T03:11:42Z","timestamp":1563419502000},"page":"3155","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Benchmarking Particle Filter Algorithms for Efficient Velodyne-Based Vehicle Localization"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9745-285X","authenticated-orcid":false,"given":"Jose Luis","family":"Blanco-Claraco","sequence":"first","affiliation":[{"name":"Engineering Department, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2878-3011","authenticated-orcid":false,"given":"Francisco","family":"Ma\u00f1as-Alvarez","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0147-9231","authenticated-orcid":false,"given":"Jose Luis","family":"Torres-Moreno","sequence":"additional","affiliation":[{"name":"Engineering Department, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9536-1922","authenticated-orcid":false,"given":"Francisco","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5167-605X","authenticated-orcid":false,"given":"Antonio","family":"Gimenez-Fernandez","sequence":"additional","affiliation":[{"name":"Engineering Department, University of Almer\u00eda, 04120 Almer\u00eda, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1177\/0278364913491297","article-title":"Vision meets robotics: The KITTI dataset","volume":"32","author":"Geiger","year":"2013","journal-title":"Int. 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