{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T06:33:31Z","timestamp":1775025211773,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,3,31]],"date-time":"2023-03-31T00:00:00Z","timestamp":1680220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Nature Science Foundation of Shaanxi","award":["2022JQ-653"],"award-info":[{"award-number":["2022JQ-653"]}]},{"name":"The Nature Science Foundation of Shaanxi","award":["D5000210767"],"award-info":[{"award-number":["D5000210767"]}]},{"name":"The Fundamental Research Funds for the Central Universities, Northwestern Polytechnical University","award":["2022JQ-653"],"award-info":[{"award-number":["2022JQ-653"]}]},{"name":"The Fundamental Research Funds for the Central Universities, Northwestern Polytechnical University","award":["D5000210767"],"award-info":[{"award-number":["D5000210767"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Visual simultaneous localization and mapping (SLAM), based on point features, achieves high localization accuracy and map construction. They primarily perform simultaneous localization and mapping based on static features. Despite their efficiency and high precision, they are prone to instability and even failure in complex environments. In a dynamic environment, it is easy to keep track of failures and even failures in work. The dynamic object elimination method, based on semantic segmentation, often recognizes dynamic objects and static objects without distinction. If there are many semantic segmentation objects or the distribution of segmentation objects is uneven in the camera view, this may result in feature offset and deficiency for map matching and motion tracking, which will lead to problems, such as reduced system accuracy, tracking failure, and track loss. To address these issues, we propose a novel point-line SLAM system based on dynamic environments. The method we propose obtains the prior dynamic region features by detecting and segmenting the dynamic region. It realizes the separation of dynamic and static objects by proposing a geometric constraint method for matching line segments, combined with the epipolar constraint method of feature points. Additionally, a dynamic feature tracking method based on Bayesian theory is proposed to eliminate the dynamic noise of points and lines and improve the robustness and accuracy of the SLAM system. We have performed extensive experiments on the KITTI and HPatches datasets to verify these claims. The experimental results show that our proposed method has excellent performance in dynamic and complex scenes.<\/jats:p>","DOI":"10.3390\/rs15071893","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T01:37:05Z","timestamp":1680485825000},"page":"1893","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["PLDS-SLAM: Point and Line Features SLAM in Dynamic Environment"],"prefix":"10.3390","volume":"15","author":[{"given":"Chaofeng","family":"Yuan","sequence":"first","affiliation":[{"name":"Unmanned Systems Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"given":"Yuelei","family":"Xu","sequence":"additional","affiliation":[{"name":"Unmanned Systems Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]},{"given":"Qing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Unmanned Systems Research Institute, Northwestern Polytechnical University, Xi\u2019an 710072, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,31]]},"reference":[{"key":"ref_1","first-page":"1403","article-title":"Real-time simultaneous localisation and mapping with a single camera","volume":"Volume 3","author":"Davison","year":"2003","journal-title":"Computer Vision, Proceedings of the IEEE International Conference on IEEE Computer Society, Nice, France, 13\u201316 October 2003"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Klein, G., and Murray, D. 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