{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:13:32Z","timestamp":1780636412563,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Plan","award":["2017YFC0602905"],"award-info":[{"award-number":["2017YFC0602905"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41572317"],"award-info":[{"award-number":["41572317"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Unmanned mining is one of the most effective methods to solve mine safety and low efficiency. However, it is the key to accurate localization and mapping for underground mining environment. A novel graph simultaneous localization and mapping (SLAM) optimization method is proposed, which is based on Generalized Iterative Closest Point (GICP) three-dimensional (3D) point cloud registration between consecutive frames, between consecutive key frames and between loop frames, and is constrained by roadway plane and loop. GICP-based 3D point cloud registration between consecutive frames and consecutive key frames is first combined to optimize laser odometer constraints without other sensors such as inertial measurement unit (IMU). According to the characteristics of the roadway, the innovative extraction of the roadway plane as the node constraint of pose graph SLAM, in addition to automatic removing the noise point cloud to further improve the consistency of the underground roadway map. A lightweight and efficient loop detection and optimization based on rules and GICP is designed. Finally, the proposed method was evaluated in four scenes (such as the underground mine laboratory), and compared with the existing 3D laser SLAM method (such as Lidar Odometry and Mapping (LOAM)). The results show that the algorithm could realize low drift localization and point cloud map construction. This method provides technical support for localization and navigation of underground mining environment.<\/jats:p>","DOI":"10.3390\/s19132915","type":"journal-article","created":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T10:54:47Z","timestamp":1561978487000},"page":"2915","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":105,"title":["Robust GICP-Based 3D LiDAR SLAM for Underground Mining Environment"],"prefix":"10.3390","volume":"19","author":[{"given":"Zhuli","family":"Ren","sequence":"first","affiliation":[{"name":"School of Resources and Safety Engineering, Central South University, Changsha 410083, China"},{"name":"Digital Mine Research Center, Central South University, Changsha 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liguan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Resources and Safety Engineering, Central South University, Changsha 410083, China"},{"name":"Digital Mine Research Center, Central South University, Changsha 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1652-5122","authenticated-orcid":false,"given":"Lin","family":"Bi","sequence":"additional","affiliation":[{"name":"School of Resources and Safety Engineering, Central South University, Changsha 410083, China"},{"name":"Digital Mine Research Center, Central South University, Changsha 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.ijrmms.2012.12.022","article-title":"Studies on temporal and spatial variation of microseismic activities in a deep metal mine","volume":"60","author":"Liu","year":"2013","journal-title":"Int. J. Rock Mech. Min. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"El Assaf, A., Zaidi, S., Affes, S., and Kandil, N. (2015, January 4\u20137). Accurate sensors localization in underground mines or tunnels. Proceedings of the 2015 IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB), Montreal, QC, Canada.","DOI":"10.1109\/ICUWB.2015.7324418"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Kumar, S.S., Jabannavar, S.S., Shashank, K.R., Nagaraj, M., and Shreenivas, B. (2017, January 22\u201324). Localization and tracking of unmanned vehicles for underground mines. Proceedings of the 2017 Second International Conference on Electrical, Computer and Communication Technologies (ICECCT), Coimbatore, India.","DOI":"10.1109\/ICECCT.2017.8117958"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1002\/rob.21504","article-title":"Efficient large-scale three-dimensional mobile mapping for underground mines","volume":"31","author":"Zlot","year":"2014","journal-title":"J. Field Robot."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Xu, Z., Yang, W., You, K., Li, W., and Kim, Y. (2017). Vehicle autonomous localization in local area of coal mine tunnel based on vision sensors and ultrasonic sensors. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0171012"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Smith, R., Self, M., and Cheeseman, P. (1990). Estimating uncertain spatial relationships in robotics. Autonomous Robot Vehicles, Springer.","DOI":"10.1007\/978-1-4613-8997-2_14"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1177\/0278364906061157","article-title":"Automatic three-dimensional underground mine mapping","volume":"25","author":"Huber","year":"2006","journal-title":"Int. J. Robot. Res."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"L\u00f3pez, E., Garc\u00eda, S., Barea, R., Bergasa, L., Molinos, E., Arroyo, R., Romera, E., and Pardo, S. (2017). A multi-sensorial simultaneous localization and mapping (SLAM) system for low-cost micro aerial vehicles in GPS-denied environments. Sensors, 17.","DOI":"10.3390\/s17040802"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.1109\/TRO.2012.2200990","article-title":"Zebedee: Design of a spring-mounted 3-d range sensor with application to mobile mapping","volume":"28","author":"Bosse","year":"2012","journal-title":"IEEE Trans. Robot."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1002\/rob.21611","article-title":"Evaluation of sensors and mapping approaches for disasters in tunnels","volume":"33","author":"Leingartner","year":"2016","journal-title":"J. Field Robot."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Moosmann, F., and Stiller, C. (2011, January 5\u20139). Velodyne SLAM. Proceedings of the 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany.","DOI":"10.1109\/IVS.2011.5940396"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1002\/rob.20204","article-title":"Scan registration for autonomous mining vehicles using 3D-NDT","volume":"24","author":"Magnusson","year":"2007","journal-title":"J. Field Robot."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0262-8856(92)90066-C","article-title":"Object modelling by registration of multiple range images","volume":"10","author":"Chen","year":"1992","journal-title":"Image Vis. Comput."},{"key":"ref_14","first-page":"586","article-title":"Method for registration of 3-D shapes","volume":"1611","author":"Besl","year":"1992","journal-title":"Sens. Fusion IV: Control Paradig. Data Struct."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Segal, A., Haehnel, D., and Thrun, S. (2009, January 25\u201328). Generalized-ICP. Proceedings of the Robotics: Science and Systems, Zurich, Switzerland.","DOI":"10.15607\/RSS.2009.V.021"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Serafin, J., and Grisetti, G. (2014, January 20\u201323). Using augmented measurements to improve the convergence of ICP. Proceedings of the International Conference on Simulation, Modeling, and Programming for Autonomous Robots, Bergamo, Italy.","DOI":"10.1007\/978-3-319-11900-7_48"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Serafin, J., and Grisetti, G. (October, January 28). NICP: Dense normal based point cloud registration. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7353455"},{"key":"ref_18","unstructured":"Censi, A., Iocchi, L., and Grisetti, G. (2005, January 18\u201322). Scan matching in the Hough domain. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1007\/s10514-016-9548-2","article-title":"Low-drift and real-time lidar odometry and mapping","volume":"41","author":"Zhang","year":"2017","journal-title":"Auton. Robot."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Shan, T., and Englot, B. (2018, January 1\u20135). LeGO-LOAM: Lightweight and ground-optimized lidar odometry and mapping on variable terrain. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594299"},{"key":"ref_21","unstructured":"Biber, P., and Stra\u00dfer, W. (2003, January 27\u201331). The normal distributions transform: A new approach to laser scan matching. Proceedings of the 2003 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No. 03CH37453), Las Vegas, NV, USA."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1109\/MITS.2010.939925","article-title":"A tutorial on graph-based SLAM","volume":"2","author":"Grisetti","year":"2010","journal-title":"IEEE Intell. Transp. Syst. Mag."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Triggs, B., McLauchlan, P.F., Hartley, R.I., and Fitzgibbon, A.W. (1999, January 20\u201325). Bundle adjustment\u2014A modern synthesis. Proceedings of the International workshop on vision algorithms, Corfu, Greece.","DOI":"10.1007\/3-540-44480-7_21"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1611","DOI":"10.1177\/0278364913498910","article-title":"Robust loop closing over time for pose graph SLAM","volume":"32","author":"Latif","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Magnusson, M., Andreasson, H., Nuchter, A., and Lilienthal, A.J. (2009, January 12\u201317). Appearance-based loop detection from 3D laser data using the normal distributions transform. Proceedings of the 2009 IEEE International Conference on Robotics and Automation, Kobe, Japan.","DOI":"10.1109\/ROBOT.2009.5152712"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1109\/TPAMI.2008.111","article-title":"Efficient visual search of videos cast as text retrieval","volume":"31","author":"Sivic","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","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_28","unstructured":"Ulrich, I., and Nourbakhsh, I. (2000, January 24\u201328). Appearance-based place recognition for topological localization. Proceedings of the 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for point-cloud shape detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ma, L., Kerl, C., St\u00fcckler, J., and Cremers, D. (2016, January 16\u201321). CPA-SLAM: Consistent plane-model alignment for direct RGB-D SLAM. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487260"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hartley, R., and Zisserman, A. (2003). Multiple View Geometry in Computer Vision, Cambridge University Press.","DOI":"10.1017\/CBO9780511811685"},{"key":"ref_32","unstructured":"K\u00fcmmerle, R., Grisetti, G., Strasdat, H., Konolige, K., and Burgard, W. (2011, January 9\u201313). g2o: A general framework for graph optimization. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s10514-012-9321-0","article-title":"OctoMap: An efficient probabilistic 3D mapping framework based on octrees","volume":"34","author":"Hornung","year":"2013","journal-title":"Auton. Robots"},{"key":"ref_34","unstructured":"Erik-Nilson (2019, June 26). Blam\u2014Berkeley Localization and Mapping. Available online: https:\/\/github.com\/erik-nelson\/blam."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/13\/2915\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:02:53Z","timestamp":1760187773000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/13\/2915"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,1]]},"references-count":34,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["s19132915"],"URL":"https:\/\/doi.org\/10.3390\/s19132915","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,1]]}}}