• 제어로봇시스템학회논문지
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• 제18권6호
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• pp.579-583
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• 2012

The purpose of this paper is to suggest IDE (Incremental Displacement Estimation) algorithm for the previously proposed visually servoed paired structured light system. The system is composed of two sides facing with each other, each with one or two lasers with a 2-DOF manipulator, a camera, and a screen. The 6-DOF displacement between two sides can be estimated by calculating the positions of the projected laser beams and rotation angles of the manipulators. In the previous study, Newton-Raphson or EKF (Extended Kalman Filter) has been used as an estimation algorithm. Although the various experimental tests have validated the performance of the system and estimation algorithms, the computation time is relatively long since aforementioned algorithms are iterative methods. Therefore, in this paper, a non-iterative incremental displacement estimation algorithm which updates the previously estimated displacement with a difference of the previous and the current observed data is introduced. To verify the performance of the algorithm, experimental tests have been performed. The results show that the proposed non-iterative algorithm estimates the displacement with the same level of accuracy compared to the EKF with multiple iterations with significantly less computation time.

• Smart Structures and Systems
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• 제9권3호
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• pp.273-286
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• 2012

As civil structures are exposed to various external loads, it is essential to assess the structural condition, especially the structural displacement, in every moment. Therefore, a visually servoed paired structured light system was proposed in the previous study. The proposed system is composed of two screens facing with each other, each with a camera, a screen, and one or two lasers controlled by a 2-DOF manipulator. The 6-DOF displacement can be calculated from the positions of three projected laser beams and the rotation angles of the manipulators. In the estimation process, one of well-known iterative methods such as Newton-Raphson or extended Kalman filter (EKF) was used for each measurement. Although the proposed system with the aforementioned algorithms estimates the displacement with high accuracy, it takes relatively long computation time. Therefore, an incremental displacement estimation (IDE) algorithm which updates the previously estimated displacement based on the difference between the previous and the current observed data is newly proposed. To validate the performance of the proposed algorithm, simulations and experiments are performed. The results show that the proposed algorithm significantly reduces the computation time with the same level of accuracy compared to the EKF with multiple iterations.