[1] Liu X Y. Research on multi-target visual recognition and positioning method for logistics warehouse sorting robot[J]. Adhesion, 47, 109-112(2021).

[2] Zhao Y S, Wu Q X, Fu S F et al. Efficient planar object recognition and localization system based on boundary point pair feature[J]. Application Research of Computers, 36, 601-605(2019).

[3] Tan G, Hua X H, Tao W Y et al. Multiview terrestrial laser scanning point cloud registration method based on laser tracker[J]. Chinese Journal of Lasers, 48, 1710002(2021).

[4] Zhao H S, Jiang L, Fu C W et al. PointWeb: enhancing local neighborhood features for point cloud processing[C], 5560-5568(2019).

[5] Yang H, Shi J N, Carlone L. TEASER: fast and certifiable point cloud registration[J]. IEEE Transactions on Robotics, 37, 314-333(2021).

[6] Rusu R B, Bradski G, Thibaux R et al. Fast 3D recognition and pose using the viewpoint feature histogram[C], 2155-2162(2010).

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

[8] Liu Y Z, Zhang Q, Lin S. Improved ICP point cloud registration algorithm based on fast point feature histogram[J]. Laser & Optoelectronics Progress, 58, 0611003(2021).

[9] Wang C, Xu D F, Zhu Y K et al. DenseFusion: 6D object pose estimation by iterative dense fusion[C], 3338-3347(2019).

[10] Drost B, Ulrich M, Navab N et al. Model globally, match locally: efficient and robust 3D object recognition[C], 998-1005(2010).

[11] Choi C, Christensen H I. 3D pose estimation of daily objects using an RGB-D camera[C], 3342-3349(2012).

[12] Liu D Y, Arai S, Miao J Q et al. Point pair feature-based pose estimation with multiple edge appearance models (PPF-MEAM) for robotic bin picking[J]. Sensors, 18, 2719(2018).

[13] Xu G Y, Dong H W, Qian J H et al. Pose estimation algorithm for random bins based on point pair features[J]. Laser & Optoelectronics Progress, 57, 181508(2020).

[14] Li X Y, Zhang Z. Research on pose detection of industrial parts based on point-pair features[J]. Journal of Changsha University of Science & Technology (Natural Science), 18, 100-107(2021).

[15] Li J T, Cheng X J, Yang Z X et al. Curvature-grading-based compression for point cloud data[J]. Laser & Optoelectronics Progress, 56, 142801(2019).

[16] Song C H, Li J R, Liu G J. Point cloud registration method using feature point sampling consistency initial alignment and improved ICP algorithm[J]. Beijing Surveying and Mapping, 35, 317-322(2021).

[17] Tian Q H, Bai R L, Li D. Point cloud segmentation of scattered workpieces based on improved euclidean clustering[J]. Laser & Optoelectronics Progress, 54, 121503(2017).

[18] Yang X W, Wang A B, Han X et al. Point cloud semantic segmentation based on KNN-PointNet[J]. Laser & Optoelectronics Progress, 58, 2410013(2021).

[19] Jing Z W, Guan H Y, Zang Y F et al. Survey of point cloud semantic segmentation based on deep learning[J]. Journal of Frontiers of Computer Science and Technology, 15, 1-26(2021).

[20] Liu R, Lü K Y, Yuan Z C et al. Plane point cloud segmentation method based on depth image and watershed[J]. Jiangxi Science, 39, 166-171(2021).

[21] Zhang W F, Han J H, Guo B J et al. Application of improved watershed algorithm in adhesion image segmentation[J]. Computer Applications and Software, 38, 243-248(2021).

[22] Li Q M, Ren J J, Pei X H et al. High-accuracy point cloud matching algorithm for weak-texture surface based on multi-modal data cooperation[J]. Acta Optica Sinica, 42, 0810001(2022).