Wang Dai-Hua, Wang Kan, Qiang Lin-Sen
Key Laboratory of Optoelectronic Technology and Systems of the Ministry of Education of China, Chongqing University, Chongqing, China.
Precision and Intelligence Laboratory, Department of Measurement and Control Technology and Instrument, Chongqing University, Chongqing, China.
J Microsc. 2021 Aug;283(2):77-92. doi: 10.1111/jmi.13010. Epub 2021 Apr 27.
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.
微零件的三维(3D)形态对主要装配毫米和微米级微零件的微装配系统的性能有重要影响。由于传统显微视觉系统无法准确获取微零件的3D形态,本文提出一种基于显微视觉层析扫描(MVTS)图像的微装配空间中微零件表面深度估计方法。该方法利用MVTS图像中聚焦值最大的像素位置构建微零件表面的等深轮廓,并通过为相应等深轮廓赋予深度值来获取MVTS位置处微零件表面的深度值。MVTS图像由MVTS获取,MVTS图像中聚焦值最大的像素通过对微装配空间中微零件的MVTS图像进行聚焦测量获得。在此基础上,应用3D空间插值方法对相邻等深轮廓之间空间的深度值进行映射,以获得微零件所有表面的深度值。通过从两个模拟对象生成模拟MVTS图像阵列进行模拟实验,验证所提方法,并分析所提方法的影响参数。在能够实现MVTS的微装配实验装置中,利用锥腔和微夹钳的端部爪进行所提深度估计方法的实验验证。使用迭代最近点配准算法将锥腔和微夹钳端部爪的深度图的3D形态与其各自的CAD模型进行配准,以量化深度估计的精度。研究结果表明,所提方法能够获取微零件的3D形态,且精度优于传统的聚焦形状法。该方法为获取微零件的形态提供了一种新途径,为提高微装配系统中抓取、对准和接近微零件的精度和效率奠定了基础。