Corner recognition of industrial robot contour curve for visual servoing

被引：0
|
作者：
Feng Y.-X. [1 ]
Li K.-J. [1 ]
Gao Y.-C. [1 ]
Zheng H. [2 ]
机构：
[1] State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou
[2] Hangzhou Innovation Institute, Beihang University, Hangzhou
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2020年 / 54卷 / 08期
关键词：
Corner recognition; Gripper; Industrial robot; Plane contour curve; Visual servo;
D O I：
10.3785/j.issn.1008-973X.2020.08.001
中图分类号：
学科分类号：
摘要：
A contour curve corner recognition algorithm was presented to solve the problem of low efficiency of corner recognition of contour curve in visual servoing of industrial robots, which affects the accuracy of real-time positioning. A coding model of gripper contour curve based on Freeman chain code is established, and the differential code is used to unify the coding model of the characteristics of contour curve angle change of gripper. The differential codes are weighted locally and the curvature values of points on the gripper contour curve are calculated to accurately quantify the identification of the corners through convolution operation based on differential codes and convolution coefficients. The preliminary selection of the selected corner points is based on the candidate corner point threshold, the distance between the farthest point of the point and the maximum point value in the local range. A burr filtering for planar contour curve is used to screen mistaken points, moreover an accurate recognition of gripper corner point is realized, which provides reliable location information for real-time positioning in visual servo system. The accuracy and efficiency of the proposed method are verified by comparing with the existing corner recognition algorithms of planar contour curves, and the corner extraction process of the proposed method has strong robustness. Copyright ©2018 Journal of Zhejiang University (Engineering Science). All rights reserved.
引用
收藏
页码：1449 / 1456
页数：7
相关论文
共 25 条
  • [1] HAJILOO A, KESHMIRI M, XIE W F, Et al., Robust on-line model predictive control for a constrained image based visual servoing, IEEE Transactions on Industrial Electronics, 63, 4, pp. 2242-2250, (2016)
  • [2] QIU Z, HU S, LIANG X., Model predictive control for constrained image-based visual servoing in uncalibrated environments, Asian Journal of Control, 21, 2, pp. 783-799, (2018)
  • [3] ANJUM F, KANWAL N, CLARK A F, Et al., Statistical evaluation of corner detectors: does the statistical test have an effect, IET Computer Vision, 12, 7, pp. 1018-1030, (2017)
  • [4] LIN X, ZHU C, ZHANG Q, Et al., Geometric mesh corner detection using triangle principle, Electronics Letters, 53, 20, pp. 1354-1356, (2017)
  • [5] LIN Ying, GONG Xiao-jing, LIU Ji-lin, Calibration method of fisheye camera based on unit eyeball, Journal of Zhejiang University: Engineering Science, 47, 8, pp. 1500-1507, (2013)
  • [6] YAO G B, CUI J, DENG K Z, Et al., Robust harris corner matching based on the quasi-homography transform and self-adaptive window for wide-baseline stereo images, IEEE Transactions on Geoscience and Remote Sensing, 56, 1, pp. 559-574, (2018)
  • [7] ZHU Le-qing, CHEN Wen-zhi, XING Rui, Et al., Robust palmprint image feature extraction method, Journal of Zhejiang University: Engineering Edition, 43, 8, pp. 1412-1418, (2009)
  • [8] KAGAMI S, OMI K, HASHIMOTO K., Alignment of a flexible sheet object with position-based and image-based visual servoing, Advanced Robotics, 30, 15, pp. 1-14, (2016)
  • [9] QIN Z, PENG W, JIA S, Et al., Precise robotic assembly for large-scale objects based on automatic guidance and alignment, IEEE Transactions on Instrumentation and Measurement, 65, 6, pp. 1398-1411, (2016)
  • [10] SHUI P L, ZHANG W C., Corner detection and classification using anisotropic directional derivative representations, IEEE Transactions on Image Processing a Publication of the IEEE Signal Processing Society, 22, 8, pp. 3204-3218, (2013)
123