{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:11:03Z","timestamp":1777705863290,"version":"3.51.4"},"reference-count":15,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,4,28]]},"abstract":"<jats:p>Traditional visual SLAM algorithms run robustly under the assumption of a static environment, but always fail in dynamic scenes, since moving objects will impair camera pose tracking. Given this, this paper presents an efficient semantic dynamic SLAM (ESD-SLAM), which is suitable for dynamic scenarios. Based on the ORB-SLAM2 framework, the ESD-SLAM we proposed employs lightweight semantic segmentation network FcHarDNet to extract semantic information, and uses the region growing algorithm to optimize the semantic segmentation boundary. Then dynamic objects are removed by combining semantic information with multi-view geometry, and it further improves the localization accuracy. Combining semantic information and depth information, a dense point cloud map of static scene is constructed to serve the planning task of mobile robot. We conduct the experiments on the public TUM RGB-D dataset and in the real-world environment. Experimental results show that the proposed algorithm can improve the performance of the ORB-SLAM2 system in dynamic scenes, and significantly improve the real-time performance compared with other same type dynamic SLAM algorithms.<\/jats:p>","DOI":"10.3233\/jifs-211615","type":"journal-article","created":{"date-parts":[[2022,3,8]],"date-time":"2022-03-08T13:42:11Z","timestamp":1646746931000},"page":"5155-5164","source":"Crossref","is-referenced-by-count":12,"title":["ESD-SLAM: An efficient semantic visual SLAM towards dynamic environments"],"prefix":"10.1177","volume":"42","author":[{"given":"Yan","family":"Xu","sequence":"first","affiliation":[{"name":"Tianjin University, School of Electrical and Information Engineering, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanyun","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin University, School of Electrical and Information Engineering, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiani","family":"Huang","sequence":"additional","affiliation":[{"name":"Tianjin University, School of Electrical and Information Engineering, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong","family":"Qin","sequence":"additional","affiliation":[{"name":"Tianjin University, School of Electrical and Information Engineering, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"6","key":"10.3233\/JIFS-211615_ref1","first-page":"1309","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 TransRobot"},{"issue":"1","key":"10.3233\/JIFS-211615_ref2","first-page":"1","article-title":"Visual SLAM algorithms:A survey from 2010 to 2016","volume":"9","author":"Taketomi","year":"2017","journal-title":"IPSJ Trans Comput Vis Appl"},{"issue":"5","key":"10.3233\/JIFS-211615_ref3","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1109\/TRO.2017.2705103","article-title":"ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras, in","volume":"33","author":"Mur-Artal","year":"2017","journal-title":"IEEE Transactions on Robotics"},{"issue":"4","key":"10.3233\/JIFS-211615_ref5","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1109\/TRO.2018.2853729","article-title":"VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator, in","volume":"34","author":"Qin","year":"2018","journal-title":"IEEE Transactions on Robotics"},{"issue":"6","key":"10.3233\/JIFS-211615_ref7","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,","volume":"24","author":"Fischler","year":"1981","journal-title":"Communications of the ACM"},{"issue":"6","key":"10.3233\/JIFS-211615_ref8","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 Transactions on Robotics"},{"issue":"3","key":"10.3233\/JIFS-211615_ref9","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/TPAMI.2017.2658577","article-title":"Direct sparse odometry,","volume":"40","author":"Engel","year":"2018","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.3233\/JIFS-211615_ref10","doi-asserted-by":"crossref","unstructured":"Saputra M.R.U. , Markham A. and Trigoni N. , Visual SLAM and Structure from Motion in Dynamic Environments: A Survey, ACM Comput Surv 51(2), Article 37, 2018.","DOI":"10.1145\/3177853"},{"issue":"4","key":"10.3233\/JIFS-211615_ref13","first-page":"2263","article-title":"RGB-D SLAM in Dynamic Environments Using Points Correlations,","volume":"2","author":"Dai","year":"2018","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"4","key":"10.3233\/JIFS-211615_ref14","doi-asserted-by":"crossref","first-page":"2263","DOI":"10.1109\/LRA.2017.2724759","article-title":"RGB-D SLAM in Dynamic Environments Using Static Point Weighting,","volume":"2","author":"Li","year":"2017","journal-title":"IEEE Robotics and Automation Letters"},{"key":"10.3233\/JIFS-211615_ref15","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.robot.2016.11.012","article-title":"Improving RGB-D SLAM in dynamic environments: A motion removal approach,","volume":"89","author":"Sun","year":"2017","journal-title":"Robotics and Autonomous Systems"},{"key":"10.3233\/JIFS-211615_ref16","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/978-3-319-16841-8_2","article-title":"Visual odometry algorithm using an RGB-D sensor and IMU in a highly dynamic environment","volume":"345","author":"Kim","journal-title":"Advances in Intelligent Systems and Computing"},{"issue":"4","key":"10.3233\/JIFS-211615_ref18","doi-asserted-by":"publisher","first-page":"4076","DOI":"10.1109\/LRA.2018.2860039","article-title":"DynaSLAM: Tracking, Mapping, and Inpainting in Dynamic Scenes","volume":"3","author":"Bescos","year":"2018","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"12","key":"10.3233\/JIFS-211615_ref21","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation, in","volume":"39","author":"Badrinarayanan","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"2","key":"10.3233\/JIFS-211615_ref26","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","article-title":"The pascal visual object classes (voc) challenge,","volume":"88","author":"Everingham","year":"2010","journal-title":"International Journal of Computer Vision"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-211615","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:45:26Z","timestamp":1777455926000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-211615"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,28]]},"references-count":15,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.3233\/jifs-211615","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,28]]}}}