• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.461-468
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• 2005

This paper proposes a wheel-assembly automation system, which assembles a wheel into a hub of a vehicle hung to a moving hanger in a car manufacturing line. A macro-micro manipulator control strategy is introduced to increase the system bandwidth and tracking accuracy to ensure insertion tolerance. A camera is equipped at the newly designed wheel gripper, which is attached at the center of the end-effector of the macro-micro manipulator and is used to measure position error of the hub of the vehicle in real time. The redundancy problem in the macro-micro manipulator is solved without complicated calculation by assigning proper functions to each part so that the macro part tracks the velocity error while the micro part regulates the fine position error. Experimental results indicate that tracking error satisfies the insertion tolerance of assembly $({\pm}1mm)$, and thus it is verified that the proposed system can be applied to the wheel assembly task on a moving hanger in the manufacturing line.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.158-163
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• 2001

Operators suffer much difficulty in manipulating micro/nano-sized objects without the assistance of human interfaces, due to the scaling effects in micro/nano world. This paper presents a micro manipulation system based on the teleoperation techniques which enables the operators to manipulate the objects with ease by transferring both human motion and manipulation skill to a micromanipulator. An experimental setup consisting of a micromanipulator operated under stereo-microscope with the help of intelligent user interface provides a tool that can be used to visualize and manipulate micro-sized 3D objects in a controlled manner. The key features of a micro manipulation system and control strategies using teleoperation techniques for handling micro objects are presented. Experimental results demonstrate the feasibility of this system in precisely controlling trapping and manipulation of micro objects based on teleoperation techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.839-846
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• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.