[1] [1] Collet A, Srinivasa S S. Efficient multi-view object recognition and full pose estimation[C]//Proceeding of 2010 IEEE International Conference on Robotics and Automation, 2010: 2050–2055.

[2] [2] Munoz E, Konishi Y, Murino V, et al. Fast 6D pose estimation for texture-less objects from a single RGB image[C]//Proceeding of 2016 IEEE International Conference on Robotics and Automation, 2016: 5623–5630.

[3] [3] Zhu M L, Derpanis K G, Yang Y F, et al. Single Image 3D object detection and pose estimation for grasping[C]//Proceeding of 2014 IEEE International Conference on Robotics and Automation, 2014: 3936–3943.

[4] [4] Bo L F, Lai K, Ren X F, et al. Object recognition with hierarchical kernel descriptors[C]//Proceedings of 2011 IEEE Conference on Computer Vision and Pattern Recognition, 2011: 1729–1736.

[5] [5] Rusu R B, Blodow N, Beetz M. Fast point feature histograms (FPFH) for 3D registration[C]//Proceeding of 2009 IEEE International Conference on Robotics and Automation, 2009: 3212–3217.

[6] [6] Braun M, Rao Q, Wang Y K, et al. Pose-RCNN: Joint object detection and pose estimation using 3D object proposals[C]// Proceeding of the 19th International Conference on Intelligent Transportation Systems (ITSC), 2016: 1546–1551.

[7] [7] Pavlakos G, Zhou X W, Chan A, et al. 6-DoF object pose from semantic keypoints[C]//Proceeding of 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017: 2011–2018.

[8] [8] Duan J, Gao X. Adaptive statistical filtering double threshholds based on improved canny operator edge detection algorithm[J]. Laser Journal, 2015, 36(1): 10–12.

[9] [9] Sánchez-Torrubia M G, Torres-Blanc C, López-Martínez M A. Pathfinder: A visualization eMathTeacher for actively learning Dijkstra's algorithm[J]. Electronic Notes in Theoretical Computer Science, 2009, 224: 151–158.

[10] [10] Richtsfeld A, Vincze M. Basic object shape detection and tracking using perceptual organization[C]//Proceeding of 2009 IEEE International Conference on Advanced Robotics, 2009: 1–6.

[11] [11] M rwald T, Prankl J, Richtsfeld A, et al. BLORT - the blocks world robotic vision toolbox[Z]. 2010: 1–8.

[12] [12] DAI J L. A research on preprocessing algorithms of mass point cloud[D]. Hangzhou: Zhejiang University, 2006.

[13] [13] Rusu R B, Cousins S. 3D is here: Point Cloud Library (PCL)[C]//Proceeding of 2011 IEEE International Conference on Robotics and Automation, 2011: 1–4.

[14] [14] Zhao T, Li H, Cai Q, et al. Point Cloud Segmentation Based on FPFH Features[C]// Proceedings of 2016 Chinese Intelligent Systems Conference. Singapore, Springer, 2016.

[15] [15] Rusu R B, Bradski G, Thibaux R, et al. Fast 3D recognition and pose using the viewpoint feature histogram[C]//Proceeding of 2010 IEEE International Conference on Intelligent Robots and Systems, 2010: 2155–2162.

[16] [16] Zhu D H. Point cloud library PCL[M]. Beijing: Beijing University of Aeronautics and Astronautics Press, 2012: 338–355.

[17] [17] Huang F S, Qin Y M, Ren Y S. The image recognition method on round bales robot labeling system[J]. Opto-Electronic Engineering, 2016, 43(12): 168–174.