Development of Vision Systems for Micro Assembly Operations

Abstract

Automated assembly relies heavily on vision systems from machine vision manufacturers like ABB. Robot control in an assembly environment where individual components range from 1 to 100 micrometers is not possible with current vision systems because current systems do not provide sufficient resolution in the workspace when they are fixed, and they are too large to be brought close enough to the components. Great accuracy and high adaptability are considered to be two of the most important benefits of a small-size D vision system. Because the micro- and nanoscale dimensions of the microminiature parts involved cannot be attained by standard cameras, it is not possible to successfully capture the picture of the parts to be assembled, therefore affecting the assembly. On the basis of micro machine vision, an image smoothing, image sharpening, image segmentation, and edge extraction method for microminiature part images was created using MATLAB software to examine the structures, identification, location, and assembly process of microminiature parts under a stereo microscope and high resolution CCD camera. The results reveal that the visual method we employed has done a fantastic job of automatically measuring and precisely
assembling small pieces.