{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T20:49:27Z","timestamp":1775076567331,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T00:00:00Z","timestamp":1676851200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["52102457"],"award-info":[{"award-number":["52102457"]}]},{"name":"National Natural Science Foundation of China","award":["2021M691207"],"award-info":[{"award-number":["2021M691207"]}]},{"name":"National Natural Science Foundation of China","award":["21QC09"],"award-info":[{"award-number":["21QC09"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["52102457"],"award-info":[{"award-number":["52102457"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2021M691207"],"award-info":[{"award-number":["2021M691207"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["21QC09"],"award-info":[{"award-number":["21QC09"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Development Plan Project of Changchun","award":["52102457"],"award-info":[{"award-number":["52102457"]}]},{"name":"Science and Technology Development Plan Project of Changchun","award":["2021M691207"],"award-info":[{"award-number":["2021M691207"]}]},{"name":"Science and Technology Development Plan Project of Changchun","award":["21QC09"],"award-info":[{"award-number":["21QC09"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>LiDAR-based simultaneous localization and mapping (SLAM) and online localization methods are widely used in autonomous driving, and are key parts of intelligent vehicles. However, current SLAM algorithms have limitations in map drift and localization algorithms based on a single sensor have poor adaptability to complex scenarios. A SLAM and online localization method based on multi-sensor fusion is proposed and integrated into a general framework in this paper. In the mapping process, constraints consisting of normal distributions transform (NDT) registration, loop closure detection and real time kinematic (RTK) global navigation satellite system (GNSS) position for the front-end and the pose graph optimization algorithm for the back-end, which are applied to achieve an optimized map without drift. In the localization process, the error state Kalman filter (ESKF) fuses LiDAR-based localization position and vehicle states to realize more robust and precise localization. The open-source KITTI dataset and field tests are used to test the proposed method. The method effectiveness shown in the test results achieves 5\u201310 cm mapping accuracy and 20\u201330 cm localization accuracy, and it realizes online autonomous driving in complex scenarios.<\/jats:p>","DOI":"10.3390\/jimaging9020052","type":"journal-article","created":{"date-parts":[[2023,2,20]],"date-time":"2023-02-20T04:58:23Z","timestamp":1676869103000},"page":"52","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["LiDAR-Based Sensor Fusion SLAM and Localization for Autonomous Driving Vehicles in Complex Scenarios"],"prefix":"10.3390","volume":"9","author":[{"given":"Kai","family":"Dai","sequence":"first","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7927-0772","authenticated-orcid":false,"given":"Bohua","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]},{"given":"Guanpu","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]},{"given":"Shuai","family":"Zhao","sequence":"additional","affiliation":[{"name":"Automotive Data Center, CATARC, Tianjin 300000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0007-0549","authenticated-orcid":false,"given":"Fangwu","family":"Ma","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]},{"given":"Yufei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]},{"given":"Jian","family":"Wu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1007\/978-3-030-75472-3_7","article-title":"A tutorial: Mobile robotics, SLAM, bayesian filter, keyframe bundle adjustment and ROS applications","volume":"6","author":"Aslan","year":"2021","journal-title":"Robot Oper. Syst. (ROS)"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1078","DOI":"10.1109\/TITS.2016.2595618","article-title":"Sensor fusion-based low-cost vehicle localization system for complex urban environments","volume":"18","author":"Suhr","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1109\/JIOT.2018.2812300","article-title":"A survey of the state-of-the-art localization techniques and their potentials for autonomous vehicle applications","volume":"5","author":"Kuutti","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"8028","DOI":"10.1109\/ACCESS.2021.3049482","article-title":"Updating Point Cloud Layer of High Definition (HD) Map Based on Crowd-Sourcing of Multiple Vehicles Installed LiDAR","volume":"9","author":"Kim","year":"2021","journal-title":"IEEE Access"},{"key":"ref_5","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_6","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1007\/s10514-013-9327-2","article-title":"Comparing ICP variants on real-world data sets","volume":"34","author":"Pomerleau","year":"2013","journal-title":"Auton. Robot."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.robot.2014.08.008","article-title":"Generic NDT mapping in dynamic environments and its application for lifelong SLAM","volume":"69","author":"Einhorn","year":"2015","journal-title":"Robot. Auton. Syst."},{"key":"ref_8","unstructured":"Zhang, J., and Singh, S. (2007). Robotics: Science and Systems, MIT Press."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1109\/LRA.2017.2651376","article-title":"Convergence and consistency analysis for a 3-D invariant-EKF SLAM","volume":"2","author":"Zhang","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ren, Z., Wang, L., and Bi, L. (2019). Robust GICP-based 3D LiDAR SLAM for underground mining environment. Sensors, 19.","DOI":"10.3390\/s19132915"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Fayyad, J., Jaradat, M.A., Gruyer, D., and Najjaran, H. (2020). Deep learning sensor fusion for autonomous vehicle perception and localization: A review. Sensors, 20.","DOI":"10.3390\/s20154220"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.1109\/TITS.2016.2627536","article-title":"Accurate attitude estimation of a moving land vehicle using low-cost MEMS IMU sensors","volume":"18","author":"Ahmed","year":"2016","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","unstructured":"Levinson, J., Montemerlo, M., and Thrun, S. (2009). Robotics: Science and Systems, MIT Press."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., and Urtasun, R. (2012, January 16\u201321). Are we ready for autonomous driving? The KITTI vision benchmark suite. Proceedings of the Computer Vision and Pattern Recognition, Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref_15","first-page":"71","article-title":"A New Variant of the ICP Algorithm for Pairwise 3D Point Cloud Registration","volume":"85","author":"Junior","year":"2022","journal-title":"Am. Acad. Sci. Res. J. Eng. Technol. Sci."},{"key":"ref_16","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_17","doi-asserted-by":"crossref","unstructured":"Ren, R., Fu, H., and Wu, M. (2019). Large-scale outdoor slam based on 2d lidar. Electronics, 8.","DOI":"10.3390\/electronics8060613"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"32310","DOI":"10.1109\/ACCESS.2021.3059866","article-title":"Robust Stereo Visual SLAM for Dynamic Environments with Moving Object","volume":"9","author":"Li","year":"2021","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wen, W., Hsu, L.-T., and Zhang, G. (2018). Performance analysis of NDT-based graph SLAM for autonomous vehicle in diverse typical driving scenarios of Hong Kong. Sensors, 18.","DOI":"10.3390\/s18113928"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6076","DOI":"10.1109\/LRA.2021.3091386","article-title":"BVMatch: LiDAR-Based place recognition using bird\u2019s-eye view images","volume":"6","author":"Luo","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1016\/j.patrec.2016.07.006","article-title":"GOOD: A global orthographic object descriptor for 3D object recognition and manipulation","volume":"83","author":"Kasaei","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1948","DOI":"10.1109\/LRA.2019.2897340","article-title":"1-day learning, 1-year localization: Long-term lidar localization using scan context image","volume":"4","author":"Kim","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Xue, G., Wei, J., Li, R., and Cheng, J. (2022). LeGO-LOAM-SC: An Improved Simultaneous Localization and Mapping Method Fusing LeGO-LOAM and Scan Context for Underground Coalmine. Sensors, 22.","DOI":"10.3390\/s22020520"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Arshad, S., and Kim, G.-W. (2021). Role of deep learning in loop closure detection for visual and lidar slam: A survey. Sensors, 21.","DOI":"10.3390\/s21041243"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1719","DOI":"10.1109\/TRO.2020.3006717","article-title":"CPL-SLAM: Efficient and certifiably correct planar graph-based SLAM using the complex number representation","volume":"36","author":"Fan","year":"2020","journal-title":"IEEE Trans. Robot."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.robot.2019.06.004","article-title":"Pose-graph SLAM sparsification using factor descent","volume":"119","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.21105\/joss.02783","article-title":"SLAM Toolbox: SLAM for the dynamic world","volume":"6","author":"Macenski","year":"2021","journal-title":"J. Open Source Softw."},{"key":"ref_28","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_29","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_30","doi-asserted-by":"crossref","unstructured":"Lin, R., Xu, J., and Zhang, J. (Ind. Robot Int. J. Robot. Res. Appl., 2021). GLO-SLAM: A slam system optimally combining GPS and LiDAR odometry, Ind. Robot Int. J. Robot. Res. Appl., ahead-of-print.","DOI":"10.1108\/IR-12-2020-0272"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Chang, L., Niu, X., and Liu, T. (2020). GNSS\/IMU\/ODO\/LiDAR-SLAM Integrated Navigation System Using IMU\/ODO Pre-Integration. Sensors, 20.","DOI":"10.3390\/s20174702"},{"key":"ref_32","unstructured":"Chen, C., Wang, B., Lu, C.X., Trigoni, N., and Markham, A. (2020). A survey on deep learning for localization and mapping: Towards the age of spatial machine intelligence. arXiv."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TCDS.2020.3038898","article-title":"Approaches challenges and applications for deep visual odometry toward to complicated and emerging areas","volume":"14","author":"Wang","year":"2020","journal-title":"IEEE Trans. Cogn. Dev. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"23286","DOI":"10.3390\/s150923286","article-title":"INS\/GPS\/LiDAR integrated navigation system for urban and indoor environments using hybrid scan matching algorithm","volume":"15","author":"Gao","year":"2015","journal-title":"Sensors"},{"key":"ref_35","unstructured":"Grupp, M. (2022, November 16). evo: Python Package for the Evaluation of Odometry and Slam. Available online: https:\/\/github.com\/MichaelGrupp\/evo."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/9\/2\/52\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:37:07Z","timestamp":1760121427000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/9\/2\/52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,20]]},"references-count":35,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["jimaging9020052"],"URL":"https:\/\/doi.org\/10.3390\/jimaging9020052","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,20]]}}}