[1] Besl P J. McKay N D. A method for registration of 3-D shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 239-256(1992).

[2] Ji S, Ren Y, Ji Z et al. An improved method for registration of point cloud[J]. Optik, 140, 451-458(2017).

[3] Huang W, John M, Kulkarni P et al. Automatic 3D image registration using voxel similarity measurements based on a genetic algorithm[J]. Proceedings of SPIE, 6144, 614430(2006).

[4] Serafin J, Grisetti G. Using extended measurements and scene merging for efficient and robust point cloud registration[J]. Robotics and Autonomous Systems, 92, 91-106(2017).

[5] Li Q S, Xiong R, Vidal-Calleja T. A GMM based uncertainty model for point clouds registration[J]. Robotics and Autonomous Systems, 91, 349-362(2017).

[6] Wang C, Shu Q, Yang Y X et al. Quick registration algorithm of point clouds using structure feature[J]. Acta Optica Sinica, 38, 0911005(2018).

[7] Tang Z R, Jiang Y, Miao C W et al. Three-dimensional point cloud registration algorithm based on factor analysis[J]. Laser & Optoelectronics Progress, 56, 191503(2019).

[8] Li C L, Dian S Y, Liu H L. Point cloud registration based on improved dynamic differential evolution algorithm[J]. Electronics Optics & Control, 26, 59-64(2019).

[9] Zhao M, Shu Q, Chen W et al. Three-dimensional point cloud registration algorithm based on l p spatial mechanics model[J]. Acta Optica Sinica, 38, 1010005(2018).

[10] Storn R, Price K. Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces[J]. Journal of Global Optimization, 11, 341-359(1997).

[11] Myronenko A, Song X B. Point set registration: coherent point drift[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 2262-2275(2010).

[12] Ying S H, Peng J G, Du S Y et al. A scale stretch method based on ICP for 3D data registration[J]. IEEE Transactions on Automation Science and Engineering, 6, 559-565(2009).

[13] Yang J L, Li H D, Jia Y D. Go-ICP: solving 3D registration efficiently and globally optimally. [C]∥2013 IEEE International Conference on Computer Vision, December 1-8, 2013, Sydney, Australia. New York: IEEE, 1457-1464(2013).

[14] Yang J L, Li H D, Campbell D et al. Go-ICP: a globally optimal solution to 3D ICP point-set registration[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 2241-2254(2016).