An important trend in manufacturing technologies is miniaturization of objects. Though micro part manufactured using monolithic fabrication has simple function for recent years, they will be more functional in the future. So diverse components with different material and complex geometry must be integrated and incompatible manufacturing processes must be used. For those reason, the microassemly technology has become important and needed. In microassembly, open loop robot control is not suitable due to kinematics error. So, in the industrial scene, manual assembly or teleoperation by human are used. Because those methods are time consuming and highly expensive methods, automated method is positively necessary. In this thesis, for the automated and high precised microassembly, visual servoing techniques are used. Visual servoing techniques have shown great promise as a control strategy capable of micro precision while compensating for the many of the problems that exist in the micro domain, including imprecisely modeled and calibrated sensors and actuators.
Microassembly using visual servoing has some problems in terms of vision sensors. For the high precise assembly, the high magnification lens should be used. It has three serious problems hat are small field of view, small depth of field and small depth resolution. This thesis focuses on small depth resolution and small depth of field. To improve depth resolution, we use stereo camera and calibrate. And the acquired depth information is used for visual servoing. To solve small depth of field, object is visually servoed into the depth of field and focused. Another problem in microassembly using visual servoing is occlusion of the feature. In this thesis, we proposed the affine transformation method which can estimate the occluded feature by visible information statistically.An important trend in manufacturing technologies is miniaturization of objects. Though micro part manufactured using monolithic fabrication has simple function for recent years, they will be more functional in the future. So diverse components with different material and complex geometry must be integrated and incompatible manufacturing processes must be used. For those reason, the microassemly technology has become important and needed. In microassembly, open loop robot control is not suitable due to kinematics error. So, in the industrial scene, manual assembly or teleoperation by human are used. Because those methods are time consuming and highly expensive methods, automated method is positively necessary. In this thesis, for the automated and high precised microassembly, visual servoing techniques are used. Visual servoing techniques have shown great promise as a control strategy capable of micro precision while compensating for the many of the problems that exist in the micro domain, including imprecisely modeled and calibrated sensors and actuators.
Microassembly using visual servoing has some problems in terms of vision sensors. For the high precise assembly, the high magnification lens should be used. It has three serious problems hat are small field of view, small depth of field and small depth resolution. This thesis focuses on small depth resolution and small depth of field. To improve depth resolution, we use stereo camera and calibrate. And the acquired depth information is used for visual servoing. To solve small depth of field, object is visually servoed into the depth of field and focused. Another problem in microassembly using visual servoing is occlusion of the feature. In this thesis, we proposed the affine transformation method which can estimate the occluded feature by visible information statistically.
