{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T10:29:03Z","timestamp":1771064943379,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T00:00:00Z","timestamp":1675900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Science and Technology Major Project of Hubei Province","award":["2021AAA010"],"award-info":[{"award-number":["2021AAA010"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>LiDAR is a crucial sensor for 3D environment perception. However, limited by the field of view of the LiDAR, it is sometimes difficult to achieve complete coverage of the environment with a single LiDAR. In this paper, we designed a spinning actuated LiDAR mapping system that is compatible with both UAV and backpack platforms and propose a tightly coupled laser\u2013inertial SLAM algorithm for it. In our algorithm, edge and plane features in the point cloud are first extracted. Then, for the significant changes in the distribution of point cloud features between two adjacent scans caused by the continuous rotation of the LiDAR, we employed an adaptive scan accumulation method to improve the stability and accuracy of point cloud registration. After feature matching, the LiDAR feature factors and IMU pre-integration factor are added to the factor graph and jointly optimized to output the trajectory. In addition, an improved loop closure detection algorithm based on the Cartographer algorithm is used to reduce the drift. We conducted exhaustive experiments to evaluate the performance of the proposed algorithm in complex indoor and outdoor scenarios. The results showed that our algorithm is more accurate than the state-of-the-art algorithms LIO-SAM and FAST-LIO2 for the spinning actuated LiDAR system, and it can achieve real-time performance.<\/jats:p>","DOI":"10.3390\/rs15040963","type":"journal-article","created":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T05:51:06Z","timestamp":1676008266000},"page":"963","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Real-Time 3D Mapping in Complex Environments Using a Spinning Actuated LiDAR System"],"prefix":"10.3390","volume":"15","author":[{"given":"Li","family":"Yan","sequence":"first","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Hubei Luojia Laboratory, Wuhan University, Wuhan 430079, China"}]},{"given":"Jicheng","family":"Dai","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}]},{"given":"Yinghao","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"}]},{"given":"Changjun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China"},{"name":"Hubei Luojia Laboratory, Wuhan University, Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,9]]},"reference":[{"key":"ref_1","first-page":"50","article-title":"LiDAR for Autonomous Driving: The Principles, Challenges, and Trends for Automotive LiDAR and Perception Systems","volume":"37","author":"Li","year":"2020","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"103250","DOI":"10.1016\/j.autcon.2020.103250","article-title":"LiDAR-equipped UAV path planning considering potential locations of defects for bridge inspection","volume":"117","author":"Bolourian","year":"2020","journal-title":"Autom. Constr."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"117484","DOI":"10.1016\/j.foreco.2019.117484","article-title":"On promoting the use of LiDAR systems in forest ecosystem research","volume":"450","author":"Beland","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Raj, T., Hanim Hashim, F., Baseri Huddin, A., Ibrahim, M.F., and Hussain, A. (2020). A survey on LiDAR scanning mechanisms. Electronics, 9.","DOI":"10.3390\/electronics9050741"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5167","DOI":"10.1109\/LRA.2021.3070251","article-title":"Towards high-performance solid-state-LiDAR-inertial odometry and mapping","volume":"6","author":"Li","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Alsadik, B., and Remondino, F. (2020). Flight planning for LiDAR-based UAS mapping applications. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9060378"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2036","DOI":"10.1109\/LRA.2021.3061387","article-title":"Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments","volume":"6","author":"Liu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5573","DOI":"10.1109\/LRA.2021.3080633","article-title":"MILIOM: Tightly Coupled Multi-Input LiDAR-Inertia Odometry and Mapping","volume":"6","author":"Nguyen","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1109\/TRO.2021.3078287","article-title":"Robust Odometry and Mapping for Multi-LiDAR Systems With Online Extrinsic Calibration","volume":"38","author":"Jiao","year":"2022","journal-title":"IEEE Trans. Robot."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhang, D., Gong, Z., Chen, Y., Zelek, J., and Li, J. (August, January 28). SLAM-based multi-sensor backpack LiDAR systems in gnss-denied environments. Proceedings of the IGARSS 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898669"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Velas, M., Spanel, M., Sleziak, T., Habrovec, J., and Herout, A. (2019). Indoor and outdoor backpack mapping with calibrated pair of velodyne LiDARs. Sensors, 19.","DOI":"10.3390\/s19183944"},{"key":"ref_12","first-page":"9","article-title":"LOAM: LiDAR Odometry and Mapping in Real-time","volume":"2","author":"Zhang","year":"2014","journal-title":"Robot. Sci. Syst."},{"key":"ref_13","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_14","first-page":"5701013","article-title":"T-LOAM: Truncated Least Squares LiDAR-Only Odometry and Mapping in Real Time","volume":"60","author":"Zhou","year":"2021","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3184","DOI":"10.1109\/LRA.2021.3062815","article-title":"BALM: Bundle Adjustment for LiDAR Mapping","volume":"6","author":"Liu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"7073","DOI":"10.1109\/LRA.2021.3092274","article-title":"LiDAR SLAM With Plane Adjustment for Indoor Environment","volume":"6","author":"Zhou","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhou, L., Wang, S., and Kaess, M. (June, January 30). \u03c0-LSAM: LiDAR smoothing and mapping with planes. Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi\u2019an, China.","DOI":"10.1109\/ICRA48506.2021.9561933"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Chen, X., Milioto, A., Palazzolo, E., Giguere, P., Behley, J., and Stachniss, C. (2019, January 3\u20138). Suma++: Efficient LiDAR-based semantic slam. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China.","DOI":"10.1109\/IROS40897.2019.8967704"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Shan, T., Englot, B., Meyers, D., Wang, W., Ratti, C., and Rus, D. (2020, January 25\u201329). Lio-sam: Tightly-coupled LiDAR inertial odometry via smoothing and mapping. Proceedings of the 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA.","DOI":"10.1109\/IROS45743.2020.9341176"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ye, H., Chen, Y., and Liu, M. (2019, January 20\u201324). Tightly coupled 3D LiDAR inertial odometry and mapping. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8793511"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1109\/LRA.2021.3064227","article-title":"Fast-lio: A fast, robust LiDAR-inertial odometry package by tightly-coupled iterated kalman filter","volume":"6","author":"Xu","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.1109\/TRO.2022.3141876","article-title":"FAST-LIO2: Fast Direct LiDAR-Inertial Odometry","volume":"38","author":"Xu","year":"2022","journal-title":"IEEE Trans. Robot."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lv, J., Hu, K., Xu, J., Liu, Y., Ma, X., and Zuo, X. (October, January 27). Clins: Continuous-time trajectory estimation for LiDAR-inertial system. Proceedings of the 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic.","DOI":"10.1109\/IROS51168.2021.9636676"},{"key":"ref_24","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_25","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1002\/rob.21614","article-title":"Continuous-Time Three-Dimensional Mapping for Micro Aerial Vehicles with a Passively Actuated Rotating Laser Scanner","volume":"33","author":"Kaul","year":"2016","journal-title":"J. Field Robot."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Park, C., Moghadam, P., Kim, S., Elfes, A., Fookes, C., and Sridharan, S. (2018, January 21\u201325). Elastic LiDAR Fusion: Dense Map-Centric Continuous-Time SLAM. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8462915"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Fang, Z., Zhao, S., and Wen, S. (August, January 31). A Real-time and Low-cost 3D SLAM System Based on a Continuously Rotating 2D Laser Scanner. Proceedings of the 2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Honolulu, HI, USA.","DOI":"10.1109\/CYBER.2017.8446162"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3585","DOI":"10.1109\/LRA.2019.2928261","article-title":"A Joint Optimization Approach of LiDAR-Camera Fusion for Accurate Dense 3-D Reconstructions","volume":"4","author":"Zhen","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2068","DOI":"10.1109\/LRA.2021.3060413","article-title":"R-LOAM: Improving LiDAR Odometry and Mapping With Point-to-Mesh Features of a Known 3D Reference Object","volume":"6","author":"Oelsch","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Karimi, M., Oelsch, M., Stengel, O., Babaians, E., and Steinbach, E. (2021). LoLa-SLAM: Low-latency LiDAR SLAM using Continuous Scan Slicing. IEEE Robot. Autom. Lett., 2248\u20132255.","DOI":"10.1109\/LRA.2021.3060721"},{"key":"ref_31","unstructured":"Benson, M., Nikolaidis, J., and Clayton, G.M. (October, January 30). Lissajous-like scan pattern for a nodding multi-beam LiDAR. Proceedings of the Dynamic Systems and Control Conference, Atlanta, GA, USA."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Lupton, T., and Sukkarieh, S. (2009, January 10\u201315). Efficient integration of inertial observations into visual SLAM without initialization. Proceedings of the 2009 IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5354267"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TRO.2016.2597321","article-title":"On-Manifold Preintegration for Real-Time Visual\u2013Inertial Odometry","volume":"33","author":"Forster","year":"2017","journal-title":"IEEE Trans. Robot."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"7285","DOI":"10.1109\/LRA.2021.3097060","article-title":"Low-Drift Odometry, Mapping and Ground Segmentation Using a Backpack LiDAR System","volume":"6","author":"Chen","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_35","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 IEEE International Conference on Robotics and Automation, Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487258"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/963\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:29:26Z","timestamp":1760120966000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/963"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,9]]},"references-count":35,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15040963"],"URL":"https:\/\/doi.org\/10.3390\/rs15040963","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,9]]}}}