Vision System for Detecting and Locating Micro-Scale Objects with Guided Cartesian Robot

Naritpon Chavitranuruk, E. Pengwang
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Abstract

This paper aims to use a vision system to detect and locate the position of microscale workpiece on the GelPak & wafer ring and command the end-effector to move to the targeted positions by using 2 sets of cameras. The object that is investigated in this design is Chip On-Sub-mount Assembly (COSA) with a footprint of ${270}\times {270}$ micrometers. The first camera is used to find the COSA's position and count the quantity of the COSA on the GelPak and wafer ring. The second camera is used to find the exact position of the COSA and then the end-effector is moved to the target position on COSA's sub-mount. The challenges in this process are accuracy, system integration, and the compliance of the GelPak and the wafer ring. With this proposed design, the performances of the system are examined and validated for the working prototype. The result of the wide camera for finding the approximate center position of the COSAs is 94% successful, the percentage of counting COSA is 90% accuracy. The XY position error from the given position compared to the center position of COSA's sub-mount is ${4}.{882}\ {\mu} {m}$ and ${8}.{206}\ {\mu}{m}$ for x and y axis respectively.
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基于导向笛卡尔机器人的微尺度目标检测与定位视觉系统
本文的目的是利用视觉系统通过2组摄像机检测和定位微型工件在GelPak & wafer环上的位置,并命令末端执行器移动到目标位置。本设计研究的对象是占地面积为${270}\乘以{270}$微米的芯片子安装组件(COSA)。第一台相机用于查找COSA的位置,并计算COSA在GelPak和晶圆环上的数量。第二个相机用于找到COSA的确切位置,然后将末端执行器移动到COSA的子mount上的目标位置。这个过程中的挑战是精度、系统集成以及GelPak和晶圆环的合规性。在此基础上,对系统的工作样机进行了性能测试和验证。广角相机计算COSA中心位置的成功率为94%,计算COSA的准确率为90%。给定位置与COSA子座中心位置的XY位置误差为${4}。{882}\ {\mu} {m}$和${8}。{206}\ {\mu}{m}$分别表示x轴和y轴。
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