{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T15:43:47Z","timestamp":1766159027123,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,9,30]],"date-time":"2022-09-30T00:00:00Z","timestamp":1664496000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["51774235","2021GY-338"],"award-info":[{"award-number":["51774235","2021GY-338"]}]},{"name":"Shaanxi Provincial Key R&amp;D General Industrial Project","award":["51774235","2021GY-338"],"award-info":[{"award-number":["51774235","2021GY-338"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Mobile robots moving fast or in scenes with poor lighting conditions often cause the loss of visual feature tracking. In coal mine tunnels, the ground is often bumpy and the lighting is uneven. During the movement of the mobile robot in this scene, there will be violent bumps. The localization technology through visual features is greatly affected by the illumination and the speed of the camera movement. To solve the localization and mapping problem in an environment similar to underground coal mine tunnels, we improve a localization and mapping algorithm based on a monocular camera and an Inertial Measurement Unit (IMU). A feature-matching method that combines point and line features is designed to improve the robustness of the algorithm in the presence of degraded scene structure and insufficient illumination. The tightly coupled method is used to establish visual feature constraints and IMU pre-integration constraints. A keyframe nonlinear optimization algorithm based on sliding windows is used to accomplish state estimation. Extensive simulations and practical environment verification show that the improved simultaneous localization and mapping (SLAM) system with a monocular camera and IMU fusion can achieve accurate autonomous localization and map construction in scenes with insufficient light such as coal mine tunnels.<\/jats:p>","DOI":"10.3390\/s22197437","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"7437","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Coupled Visual and Inertial Measurement Units Method for Locating and Mapping in Coal Mine Tunnel"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4757-4194","authenticated-orcid":false,"given":"Daixian","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kangkang","family":"Ji","sequence":"additional","affiliation":[{"name":"College of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9589-7900","authenticated-orcid":false,"given":"Dong","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Communication and Information Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shulin","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electrical and Control Engineering, Xi\u2019an University of Science and Technology, Xi\u2019an 710054, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"ref_1","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 Trans. Robot."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Hess, W., Kohler, D., Rapp, H., and Andor, D. (2016, January 16\u201321). Real-Time Loop Closure in 2D LIDAR SLAM. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487258"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ding, W., Hou, S., Gao, H., Wan, G., and Song, S. (August, January 31). LiDAR Inertial Odometry Aided Robust LiDAR Localization System in Changing City Scenes. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196698"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Tarokh, M., Merloti, P., Duddy, J., and Lee, M. (December, January 30). Vision Based Robotic Person Following under Lighting Variations. Proceedings of the 2008 3rd International Conference on Sensing Technology, Taipei, Taiwan.","DOI":"10.1109\/ICSENST.2008.4757090"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive Image Features from Scale-Invariant Keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1007\/11744023_32","article-title":"SURF: Speeded Up Robust Features","volume":"Volume 3951","author":"Leonardis","year":"2006","journal-title":"Computer Vision\u2014ECCV 2006"},{"key":"ref_7","unstructured":"Harris, C., and Stephens, M. (September, January 31). A Combined Corner and Edge Detector. Proceedings of the Fourth Alvey Vision Conference, Manchester, UK."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011, January 6\u201313). ORB: An Efficient Alternative to SIFT or SURF. Proceedings of the 2011 International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_9","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","volume":"33","author":"Tardos","year":"2017","journal-title":"IEEE Trans. Robot."},{"key":"ref_10","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 Trans. Pattern Anal. Mach. Intell."},{"key":"ref_11","first-page":"283","article-title":"Robust and Efficient Visual-Inertial Odometry with Multi-Plane Priors","volume":"Volume 11859","author":"Lin","year":"2019","journal-title":"Pattern Recognition and Computer Vision"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Xie, X., Zhang, X., Fu, J., Jiang, D., Yu, C., and Jin, M. (2018). Location Recommendation of Digital Signage Based on Multi-Source Information Fusion. Sustainability, 10.","DOI":"10.3390\/su10072357"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Pumarola, A., Vakhitov, A., Agudo, A., Sanfeliu, A., and Moreno-Noguer, F. (June, January 29). PL-SLAM: Real-Time Monocular Visual SLAM with Points and Lines. Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore.","DOI":"10.1109\/ICRA.2017.7989522"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1874","DOI":"10.1109\/TRO.2021.3075644","article-title":"ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual\u2013Inertial, and Multimap SLAM","volume":"37","author":"Campos","year":"2021","journal-title":"IEEE Trans. Robot."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Von Stumberg, L., Usenko, V., and Cremers, D. (2018, January 21\u201325). Direct Sparse Visual-Inertial Odometry Using Dynamic Marginalization. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia.","DOI":"10.1109\/ICRA.2018.8462905"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mourikis, A.I., and Roumeliotis, S.I. (2007, January 10\u201314). A Multi-State Constraint Kalman Filter for Vision-Aided Inertial Navigation. Proceedings of the Proceedings 2007 IEEE International Conference on Robotics and Automation, Rome, Italy.","DOI":"10.1109\/ROBOT.2007.364024"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1177\/0278364914554813","article-title":"Keyframe-Based Visual\u2013Inertial Odometry Using Nonlinear Optimization","volume":"34","author":"Leutenegger","year":"2015","journal-title":"Int. J. Robot. Res."},{"key":"ref_18","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","volume":"34","author":"Qin","year":"2018","journal-title":"IEEE Trans. Robot."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1177\/0278364915620033","article-title":"The EuRoC Micro Aerial Vehicle Datasets","volume":"35","author":"Burri","year":"2016","journal-title":"Int. J. Robot. Res."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Allak, E., Jung, R., and Weiss, S. (2019, January 3\u20138). Covariance Pre-Integration for Delayed Measurements in Multi-Sensor Fusion. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China.","DOI":"10.1109\/IROS40897.2019.8967886"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Deschaud, J.-E. (2018, January 21\u201325). IMLS-SLAM: Scan-to-Model Matching Based on 3D Data. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia.","DOI":"10.1109\/ICRA.2018.8460653"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/978-3-642-15552-9_14","article-title":"Adaptive and Generic Corner Detection Based on the Accelerated Segment Test","volume":"Volume 6312","author":"Daniilidis","year":"2010","journal-title":"Computer Vision\u2014ECCV 2010"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1188","DOI":"10.1109\/TRO.2012.2197158","article-title":"Bags of Binary Words for Fast Place Recognition in Image Sequences","volume":"28","author":"Tardos","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1007\/978-3-642-15561-1_56","article-title":"BRIEF: Binary Robust Independent Elementary Features","volume":"Volume 6314","author":"Daniilidis","year":"2010","journal-title":"Computer Vision\u2014ECCV 2010"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/TPAMI.2008.300","article-title":"LSD: A Fast Line Segment Detector with a False Detection Control","volume":"32","author":"Jakubowicz","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1016\/j.jvcir.2013.05.006","article-title":"An Efficient and Robust Line Segment Matching Approach Based on LBD Descriptor and Pairwise Geometric Consistency","volume":"24","author":"Zhang","year":"2013","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Brickwedde, F., Abraham, S., and Mester, R. (2019, January 17\u201319). Mono-SF: Multi-View Geometry Meets Single-View Depth for Monocular Scene Flow Estimation of Dynamic Traffic Scenes. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00287"},{"key":"ref_28","unstructured":"Vijayanarasimhan, S., Ricco, S., Schmid, C., Sukthankar, R., and Fragkiadaki, K. (2017). SfM-Net: Learning of Structure and Motion from Video. arXiv."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1109\/LRA.2021.3136241","article-title":"Tightly-Coupled Magneto-Visual-Inertial Fusion for Long Term Localization in Indoor Environment","volume":"7","author":"Coulin","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1287\/ijoc.2020.0993","article-title":"Mixed-Integer Convex Nonlinear Optimization with Gradient-Boosted Trees Embedded","volume":"33","author":"Mistry","year":"2021","journal-title":"INFORMS J. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Braverman, V., Drineas, P., Musco, C., Musco, C., Upadhyay, J., Woodruff, D.P., and Zhou, S. (2020, January 16\u201319). Near Optimal Linear Algebra in the Online and Sliding Window Models. Proceedings of the 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS), Durham, NC, USA.","DOI":"10.1109\/FOCS46700.2020.00055"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"MacTavish, K., Paton, M., and Barfoot, T.D. (June, January 29). Visual Triage: A Bag-of-Words Experience Selector for Long-Term Visual Route Following. Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore.","DOI":"10.1109\/ICRA.2017.7989238"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Forster, C., Carlone, L., Dellaert, F., and Scaramuzza, D. (2022, August 09). IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation. 10 May 2015; p.10. Available online: http:\/\/hdl.handle.net\/1853\/55417.","DOI":"10.15607\/RSS.2015.XI.006"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7437\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:44:32Z","timestamp":1760143472000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/19\/7437"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,30]]},"references-count":33,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["s22197437"],"URL":"https:\/\/doi.org\/10.3390\/s22197437","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,9,30]]}}}