{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:13:44Z","timestamp":1760145224532,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Science and Technology of Heilongjiang Province","award":["2023ZX01A21","NSFC. 61803118"],"award-info":[{"award-number":["2023ZX01A21","NSFC. 61803118"]}]},{"name":"National Natural Science Foundation of China","award":["2023ZX01A21","NSFC. 61803118"],"award-info":[{"award-number":["2023ZX01A21","NSFC. 61803118"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>LiDAR-based simultaneous localization and mapping (SLAM) offer robustness against illumination changes, but the inherent sparsity of LiDAR point clouds poses challenges for continuous tracking and navigation, especially in feature-deprived scenarios. This paper proposes a novel LiDAR\/SINS tightly integrated SLAM algorithm designed to address the localization challenges in urban environments characterized in sparse structural features. Firstly, the method extracts edge points from the LiDAR point cloud using a traditional segmentation method and clusters them to form distinctive edge lines. Then, a rotation-invariant feature\u2014line distance\u2014is calculated based on the edge line properties that were inspired by the traditional tightly integrated navigation system. This line distance is utilized as the observation in a Kalman filter that is integrated into a tightly coupled LiDAR\/SINS system. This system tracks the same edge lines across multiple frames for filtering and correction instead of tracking points or LiDAR odometry results. Meanwhile, for loop closure, the method modifies the common SCANCONTEXT algorithm by designating all bins that do not reach the maximum height as special loop keys, which reduce false matches. Finally, the experimental validation conducted in urban environments with sparse structural features demonstrated a 17% improvement in positioning accuracy when compared to the conventional point-based methods.<\/jats:p>","DOI":"10.3390\/rs16142527","type":"journal-article","created":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T13:34:38Z","timestamp":1720618478000},"page":"2527","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Enhanced Strapdown Inertial Navigation System (SINS)\/LiDAR Tightly Integrated Simultaneous Localization and Mapping (SLAM) for Urban Structural Feature Weaken Occasions in Vehicular Platform"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7316-3412","authenticated-orcid":false,"given":"Xu","family":"Xu","sequence":"first","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8803-910X","authenticated-orcid":false,"given":"Lianwu","family":"Guan","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanbin","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufei","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhejun","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,10]]},"reference":[{"key":"ref_1","unstructured":"Montemerlo, M., Thrun, S., Koller, D., and Wegbreit, B. (August, January 28). Fast SLAM: A factored solution to the simultaneous localization and mapping problem. Proceedings of the AAAI-02: Eighteenth National Conference on Artificial Intelligence, Edmonton, AL, Canada."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Huang, L. (2021, January 14). Review on LiDAR-based SLAM techniques. Proceedings of the 2021 International Conference on Signal Processing and Machine Learning (CONF-SPML), Stanford, CA, USA.","DOI":"10.1109\/CONF-SPML54095.2021.00040"},{"key":"ref_3","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_4","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_5","unstructured":"Rusinkiewicz, S., and Levoy, M. (June, January 28). Efficient Variants of the ICP Algorithm. Proceedings of the of the Third International Conference on 3-D Digital Imaging and Modeling, Quebec City, QC, Canada."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1109\/TVLSI.2021.3049520","article-title":"Dynamic workload allocation for edge computing","volume":"29","author":"Hung","year":"2021","journal-title":"IEEE Trans. Very Large-Scale Integr. (VLSI) Syst."},{"key":"ref_7","first-page":"3167","article-title":"An Optimized FPGA-Based Real-Time NDT for 3D-LiDAR Localization in Smart Vehicles","volume":"68","author":"Deng","year":"2021","journal-title":"IEEE Trans. Circuits Syst. II: Express Briefs"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jiang, M., Song, S., Li, Y., Liu, J., and Feng, X. (2018, January 9\u201311). Scan registration for mechanical scanning imaging sonar using kD2D-NDT. Proceedings of the 2018 Chinese Control and Decision Conference (CCDC), Shenyang, China.","DOI":"10.1109\/CCDC.2018.8408259"},{"key":"ref_9","first-page":"1","article-title":"LOAM: Lidar odometry and mapping in real-time","volume":"2","author":"Zhang","year":"2014","journal-title":"Robot. Sci. Syst."},{"key":"ref_10","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_11","doi-asserted-by":"crossref","unstructured":"He, L., Wang, X., and Zhang, H. (2016, January 9\u201314). M2DP: A novel 3D point cloud descriptor and its application in loop closure detection. Proceedings of the 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Republic of Korea.","DOI":"10.1109\/IROS.2016.7759060"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kim, G., and Kim, A. (2018, January 1\u20135). Scan Context: Egocentric Spatial Descriptor for Place Recognition within 3D Point Cloud Map. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8593953"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1109\/TRO.2021.3116424","article-title":"Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments","volume":"38","author":"Kim","year":"2022","journal-title":"IEEE Trans. Robot."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wang, H., Wang, C., Chen, C.L., and Xie, L. (October, January 27). F-loam: Fast lidar odometry and mapping. Proceedings of the 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic.","DOI":"10.1109\/IROS51168.2021.9636655"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"16710","DOI":"10.3390\/s150716710","article-title":"Lidar scan matching aided inertial navigation system in gnss-denied environments","volume":"15","author":"Tang","year":"2015","journal-title":"Sensors"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Xu, X., Zhang, L., Yang, J., Cao, C., Wang, W., Ran, Y., Tan, Z., and Luo, M. (2022). A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR. Remote Sens., 14.","DOI":"10.3390\/rs14122835"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Koide, K., Yokozuka, M., Oishi, S., and Banno, A. (2022, January 23\u201327). Globally consistent and tightly coupled 3D LiDAR inertial mapping. Proceedings of the 2022 International Conference on Robotics and Automation (ICRA), Philadelphia, PA, USA.","DOI":"10.1109\/ICRA46639.2022.9812385"},{"key":"ref_18","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_19","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1007\/s10291-014-0415-3","article-title":"Tightly coupled integration of GPS precise point positioning and MEMS-based inertial systems","volume":"19","author":"Rabbou","year":"2015","journal-title":"GPS Solut."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Rong, H., Gao, Y., Guan, L., Ramirez-Serrano, A., Xu, X., and Zhu, Y. (2021). Point-Line Visual Stereo SLAM Using EDlines and PL-BoW. Remote Sens., 13.","DOI":"10.3390\/rs13183591"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wang, H., Guan, L., Yu, X., and Zhang, Z. (2022, January 7\u201310). PL-ISLAM: An Accurate Monocular Visual-Inertial SLAM with Point and Line Features. Proceedings of the 2022 IEEE International Conference on Mechatronics and Automation (ICMA), Guilin, China.","DOI":"10.1109\/ICMA54519.2022.9855993"},{"key":"ref_22","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 2007 IEEE International Conference on Robotics and Automation, Roma, Italy.","DOI":"10.1109\/ROBOT.2007.364024"},{"key":"ref_23","unstructured":"(2024, July 06). 32\/16-Line Mechanical Line Mechanical LiDAR|Leishen Intelligent System. Available online: https:\/\/www.lslidar.com\/product\/c32-16-mechanical-lidar\/."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Himmelsbach, M., Hundelshausen, F.V., and Wuensche, H.-J. (2010, January 21\u201324). Fast Segmentation of 3D Point Clouds for Ground Vehicles. Proceedings of the IEEE Intelligent Vehicles Symposium, La Jolla, CA, USA.","DOI":"10.1109\/IVS.2010.5548059"},{"key":"ref_25","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":"Commun. ACM"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bogoslavskyi, I., and Stachniss, C. (2016, January 9\u201314). Fast Range Image-based Segmentation of Sparse 3D Laser Scans for Online Operation. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Daejeon, Republic of Korea.","DOI":"10.1109\/IROS.2016.7759050"},{"key":"ref_27","unstructured":"Arthur, D., and Vassilvitskii, S. (2007, January 7\u20139). k-means++: The advantages of careful seeding. Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete algorithms (SODA), New Orleans, LA, USA."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1109\/34.993558","article-title":"Shape matching and object recognition using shape contexts","volume":"24","author":"Belongie","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_29","first-page":"3560","article-title":"Enhanced MEMS SINS aided pipeline surveying system by pipeline junction detection in small diameter pipeline","volume":"50","author":"Guan","year":"2017","journal-title":"IFAC-Pap."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/14\/2527\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:12:42Z","timestamp":1760109162000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/14\/2527"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":29,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["rs16142527"],"URL":"https:\/\/doi.org\/10.3390\/rs16142527","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,7,10]]}}}