[1] Yang B S, Liang F X, Huang R G. Progress, challenges and perspectives of 3D LiDAR point cloud processing[J]. Acta Geodaetica et Cartographica Sinica, 46, 1509-1516(2017).

[2] Cheng L, Chen S, Liu X Q et al. Registration of laser scanning point clouds: a review[J]. Sensors, 18, 1641(2018).

[3] Yin H S, Pei S, Xu L et al. Review on simultaneous positioning and mapping technology of multi-robot vision[J]. Journal of Mechanical Engineering, 58, 11-36(2022).

[4] Wei S F, Liu Z B, Zhao J H et al. A review of indoor 3D reconstruction with SLAM[J]. Science of Surveying and Mapping, 43, 15-26(2018).

[5] Huang R, Xu Y S, Yao W et al. Robust global registration of point clouds by closed-form solution in the frequency domain[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 171, 310-329(2021).

[6] Wang B Q, Kang Z Z. Self-closure global registration for subway tunnel point clouds[C], 152-157(2013).

[7] Kelbe D, van Aardt J, Romanczyk P et al. Marker-free registration of forest terrestrial laser scanner data pairs with embedded confidence metrics[J]. IEEE Transactions on Geoscience and Remote Sensing, 54, 4314-4330(2016).

[8] Kelbe D, van Aardt J, Romanczyk P et al. Multiview marker-free registration of forest terrestrial laser scanner data with embedded confidence metrics[J]. IEEE Transactions on Geoscience and Remote Sensing, 55, 729-741(2017).

[9] Glira P, Pfeifer N, Briese C et al. Rigorous strip adjustment of airborne laserscanning data based on the ICP algorithm[J]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3/W5, 73-80(2015).

[10] Chen Z Q, Li J P, Yang B S. A strip adjustment method of UAV-borne LiDAR point cloud based on DEM features for mountainous area[J]. Sensors, 21, 2782(2021).

[11] Yan L, Dai J C, Tan J X et al. Global fine registration of point cloud in LiDAR SLAM based on pose graph[J]. Acta Geodaetica et Cartographica Sinica, 48, 313-321(2019).

[12] Lu S D, Tu M Y, Luo X Y et al. Laser SLAM pose optimization algorithm based on graph optimization theory and GNSS[J]. Laser & Optoelectronics Progress, 57, 081024(2020).

[13] Kümmerle R, Grisetti G, Strasdat H et al. G2o: a general framework for graph optimization[C], 3607-3613(2011).

[14] Zhou Z G, Cao J W, Di S F. Overview of 3D lidar SLAM algorithms[J]. Chinese Journal of Scientific Instrument, 42, 13-27(2021).

[15] Wang Z L, Zhao J, Cai H G. A survey of back-end optimization method for graph-based SLAM under large-scale environment[J]. Journal of Harbin Institute of Technology, 47, 20-25(2015).

[16] Grisetti G, Kümmerle R, Stachniss C et al. Hierarchical optimization on manifolds for online 2D and 3D mapping[C], 273-278(2010).

[17] Konolige K, Grisetti G, Kümmerle R et al. Efficient sparse pose adjustment for 2D mapping[C], 22-29(2010).

[18] Wohlkinger W, Vincze M. Ensemble of shape functions for 3D object classification[C], 2987-2992(2012).

[19] Dong Z, Yang B S, Liang F X et al. Hierarchical registration of unordered TLS point clouds based on binary shape context descriptor[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 61-79(2018).

[20] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C], 3212-3217(2009).

[21] Xiong F G, Huo W, Han X et al. Removal method of mismatching keypoints in 3D point cloud[J]. Acta Optica Sinica, 38, 0210003(2018).

[22] Li R Z, Yang M, Tian Y et al. Point cloud registration algorithm based on the ISS feature points combined with improved ICP algorithm[J]. Laser & Optoelectronics Progress, 54, 111503(2017).

[23] Xu W, Cai Y X, He D J et al. FAST-LIO2: fast direct LiDAR-inertial odometry[J]. IEEE Transactions on Robotics, 38, 2053-2073(2022).