Wang DH, Wang K, Qiang LS. Depth estimation method of surface of micropart in microassembly space based on microscopic vision tomographic scanning images.
J Microsc 2021;
283:77-92. [PMID:
33792928 DOI:
10.1111/jmi.13010]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/20/2021] [Accepted: 03/25/2021] [Indexed: 11/26/2022]
Abstract
Three-dimensional (3D) morphology of microparts has an important influence on performance of microassembly system that mainly assembles microparts in millimetre and micron scale. Because 3D morphology of microparts cannot be accurately obtained by conventional microscopic vision system, a depth estimation method of surface of micropart in microassembly space based on microscopic vision tomographic scanning (MVTS) images is proposed in this paper. The proposed method uses the positions of pixels with the largest focus values in MVTS image to construct the isodepth contours of surface of micropart and obtains the depth values of micropart's surface at the positions of MVTS by assigning depth values to corresponding isodepth contours. The MVTS images are obtained by MVTS and pixels with the largest focus values in MVTS image are obtained by focus measurement of MVTS images of micropart in microassembly space. On these bases, 3D spatial interpolation method is applied to map depth value of space between adjacent isodepth contours and to obtain depth values of all surface of micropart. Simulation experiments are carried out to verify the proposed method by generating simulated MVTS image array from two simulation objects, and the influence parameters of the proposed method are analysed. In established experimental setup of microassembly that can realise MVTS, experimental verification for the proposed depth estimation method are carried out by using cone cavity and end jaws of microgripper. 3D morphologies of depth maps of cone cavity and end jaws of microgripper are registered with their respective CAD models using iterative nearest point registration algorithm to quantify accuracy of depth estimation. The research results show that 3D morphology of micropart can be obtained by the proposed method and has better accuracy than those by conventional shape from focus method. This method provides a new way to obtain the morphology of microparts and lays a foundation for improving the accuracy and efficiency of gripping, alignment and approaching microparts in microassembly systems.
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