{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T17:19:50Z","timestamp":1771953590607,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T00:00:00Z","timestamp":1720742400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Longmen laboratory project","award":["LMFKCY2023001"],"award-info":[{"award-number":["LMFKCY2023001"]}]},{"name":"Longmen laboratory project","award":["LMFKCY2023002"],"award-info":[{"award-number":["LMFKCY2023002"]}]},{"name":"Longmen laboratory project","award":["52075150"],"award-info":[{"award-number":["52075150"]}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["LMFKCY2023001"],"award-info":[{"award-number":["LMFKCY2023001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["LMFKCY2023002"],"award-info":[{"award-number":["LMFKCY2023002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Nature Science Foundation of China","doi-asserted-by":"publisher","award":["52075150"],"award-info":[{"award-number":["52075150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Simultaneous Localization and Mapping (SLAM) is one of the key technologies with which to address the autonomous navigation of mobile robots, utilizing environmental features to determine a robot\u2019s position and create a map of its surroundings. Currently, visual SLAM algorithms typically yield precise and dependable outcomes in static environments, and many algorithms opt to filter out the feature points in dynamic regions. However, when there is an increase in the number of dynamic objects within the camera\u2019s view, this approach might result in decreased accuracy or tracking failures. Therefore, this study proposes a solution called YPL-SLAM based on ORB-SLAM2. The solution adds a target recognition and region segmentation module to determine the dynamic region, potential dynamic region, and static region; determines the state of the potential dynamic region using the RANSAC method with polar geometric constraints; and removes the dynamic feature points. It then extracts the line features of the non-dynamic region and finally performs the point\u2013line fusion optimization process using a weighted fusion strategy, considering the image dynamic score and the number of successful feature point\u2013line matches, thus ensuring the system\u2019s robustness and accuracy. A large number of experiments have been conducted using the publicly available TUM dataset to compare YPL-SLAM with globally leading SLAM algorithms. The results demonstrate that the new algorithm surpasses ORB-SLAM2 in terms of accuracy (with a maximum improvement of 96.1%) while also exhibiting a significantly enhanced operating speed compared to Dyna-SLAM.<\/jats:p>","DOI":"10.3390\/s24144517","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T14:04:35Z","timestamp":1720793075000},"page":"4517","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["YPL-SLAM: A Simultaneous Localization and Mapping Algorithm for Point\u2013line Fusion in Dynamic Environments"],"prefix":"10.3390","volume":"24","author":[{"given":"Xinwu","family":"Du","sequence":"first","affiliation":[{"name":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China"},{"name":"Longmen Laboratory, Luoyang 471000, China"},{"name":"Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province, Luoyang 471003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenglin","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaihang","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiufang","family":"Yu","sequence":"additional","affiliation":[{"name":"College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3670-6043","authenticated-orcid":false,"given":"Shusong","family":"Wang","sequence":"additional","affiliation":[{"name":"Longmen Laboratory, Luoyang 471000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Favorskaya, M.N. 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