{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:23:24Z","timestamp":1754155404361,"version":"3.41.2"},"reference-count":27,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2014,5,13]],"date-time":"2014-05-13T00:00:00Z","timestamp":1399939200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,5,13]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 The purpose of this paper is to present a Rao\u2013Blackwellized particle filter (RBPF) approach for the visual simultaneous localization and mapping (SLAM) of small unmanned aerial vehicles (UAVs). <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 Measurements from inertial measurement unit, barometric altimeter and monocular camera are fused to estimate the state of the vehicle while building a feature map. In this SLAM framework, an extra factorization method is proposed to partition the vehicle model into subspaces as the internal and external states. The internal state is estimated by an extended Kalman filter (EKF). A particle filter is employed for the external state estimation and parallel EKFs are for the map management. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 Simulation results indicate that the proposed approach is more stable and accurate than other existing marginalized particle filter-based SLAM algorithms. Experiments are also carried out to verify the effectiveness of this SLAM method by comparing with a referential global positioning system\/inertial navigation system. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 The main contribution of this paper is the theoretical derivation and experimental application of the Rao\u2013Blackwellized visual SLAM algorithm with vehicle model partition for small UAVs.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/ir-07-2013-378","type":"journal-article","created":{"date-parts":[[2014,7,10]],"date-time":"2014-07-10T10:31:11Z","timestamp":1404988271000},"page":"266-274","source":"Crossref","is-referenced-by-count":6,"title":["Rao-Blackwellized visual SLAM for small UAVs with vehicle model partition"],"prefix":"10.1108","volume":"41","author":[{"given":"Tianmiao","family":"Wang","sequence":"first","affiliation":[]},{"given":"Chaolei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Jianhong","family":"Liang","sequence":"first","affiliation":[]},{"given":"Yicheng","family":"Zhang","sequence":"first","affiliation":[]}],"member":"140","reference":[{"key":"key2020123121145142600_b1","doi-asserted-by":"crossref","unstructured":"Ahn, S.\n               , \n                  Choi, M.\n               , \n                  Choi, J.\n                and \n                  Kyun Chung, W.\n                (2006), \u201cData association using visual object recognition for EKF-SLAM in home environment\u201d, in 2006 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Beijing, pp. 2588-2594.","DOI":"10.1109\/IROS.2006.281936"},{"key":"key2020123121145142600_b2","doi-asserted-by":"crossref","unstructured":"Artieda, J.\n               , \n                 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