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首页> 外文会议>2014 International Symposium on Optomechatronic Technologies >Characterization of Model-Based Visual Tracking Techniques for MOEMS Using a New Block Set for MATLAB/Simulink
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Characterization of Model-Based Visual Tracking Techniques for MOEMS Using a New Block Set for MATLAB/Simulink

机译：使用新的MATLAB / Simulink块集对MOEMS基于模型的视觉跟踪技术进行表征

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摘要

Micro assembly is an innovative alternative to the micro fabrication process of MOEMS which is quite complex. It usually implies the usage of micro robots controlled by an operator. The reliability of this approach has been already confirmed for the micro-optical technologies. However, the characterization of assemblies has shown that the operator is the main source of inaccuracies in the teleoperated micro assembly, so there is a great interest in automating the micro assembly process. One of the constraints of automation in micro scale is the lack of high precision sensors capable to provide the full information about the object position. Thus, the usage of visual based feedback represents a very promising approach allowing to automate the micro assembly process. The purpose of this paper is to characterize the techniques of object position estimation based on the visual data, i.e. Visual tracking techniques from the ViSP library. These algorithms allows to get the 3D object pose using a single view of the scene and the CAD model of the object. The performance of three main types of model based trackers is analyzed and quantified: edge-based, texture based and hybrid tracker. The problems of visual tracking in micro scale are discussed. The control of the micromanipulation station used in the framework of our project is performed using a new Simulink block set. Experimental results are shown and demonstrate the possibility to obtain the repeatability below 1 μm.
机译：微型组装是MOEMS微型制造过程的创新替代方案，这非常复杂。这通常意味着使用由操作员控制的微型机器人。这种方法的可靠性已经在微光学技术中得到证实。但是，装配体的特征表明，操作员是远程操作微型装配体中不准确的主要根源，因此对自动化微型装配过程产生了极大的兴趣。微型自动化的制约因素之一是缺少能够提供有关物体位置的完整信息的高精度传感器。因此，基于视觉的反馈的使用代表了一种非常有前途的方法，可以使微型装配过程自动化。本文的目的是描述基于视觉数据的对象位置估计技术，即ViSP库中的视觉跟踪技术。这些算法允许使用场景的单一视图和对象的CAD模型获得3D对象姿势。分析和量化了三种主要的基于模型的跟踪器的性能：基于边缘的，基于纹理的和混合跟踪器。讨论了微观规模的视觉跟踪问题。使用新的Simulink块集执行在我们的项目框架中使用的微操纵站的控制。显示了实验结果，并证明了获得低于1μm的重复性的可能性。

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