Positioning of Autonomous Modeling Manipulator for Deformed Surface Using Moments-based Visual Servoing

doi:10.3901/JME.2019.14.169

Abstract

Abstract: The surface depth information of the deformed surface target cannot be parameterized, which is the main reason why it is difficult to establish the image interaction matrix of moment feature. Therefore, a new method for constructing the nonparametric interaction matrix of the traditional image moment is derived based on the target contour depth information. Considering that the traditional moment based visual servo control has slow response speed and small convergence range, a novel depth moment is designed as the visual servo image feature, and its non-parametric interaction matrix is derived. The visual servo controller is designed using the steepest descent method, and dynamic performance of the two moment feature based visual servo control methods in the process of profiled surface positioning is analyzed and compared. The results show that nonparametric form of both the traditional moment interaction matrix and the depth moment interaction matrix are effective. Both methods are asymptotically stable in the control process. Compared with the traditional moment feature based visual servo method, the depth moment based visual servo improves the convergence speed and convergence range.

Key words: autonomous modeling, deformed surface, moments-based visual servoing, positioning

CLC Number:

TP13

PENG Weixing, WANG Yaonan, ZENG Kai, WU Haotian. Positioning of Autonomous Modeling Manipulator for Deformed Surface Using Moments-based Visual Servoing[J]. Journal of Mechanical Engineering, 2019, 55(14): 169-177.

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