• 한국생산제조학회지
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• 제26권1호
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• pp.50-58
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• 2017

This paper proposes a real-time robotic vision control scheme using the weighting matrix to efficiently process the vision data obtained during robotic movement to a target. This scheme is based on the vision system model that can actively control the camera parameter and robotic position change over previous studies. The vision control algorithm involves parameter estimation, joint angle estimation, and weighting matrix models. To demonstrate the effectiveness of the proposed control scheme, this study is divided into two parts: not applying the weighting matrix and applying the weighting matrix to the vision data obtained while the camera is moving towards the target. Finally, the position accuracy of the two cases is compared by performing the slender bar placement task experimentally.

• 한국정밀공학회지
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• 제33권4호
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• pp.295-301
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• 2016

The out-of-squareness is one of the error sources that affect the positioning accuracy of machine tools and coordinate measuring machines. Laser interferometer is widely used to measure the position and angular errors, and can measure the squareness using an optical square. However, the squareness measurement using the laser interferometer is difficult, as compared to other errors due to complicated optics setup and Abbe's error occurrence. The effect of out-of-squareness mainly appears at the face-diagonal of the movable plane. The diagonal displacements are also affected by the position dependent geometric errors. In this study, the squareness estimation techniques via diagonal displacement measurement using the laser interferometer without an optical square were proposed. For accurate estimation and measurement time reduction, the errors selected from proposed discriminant were measured. Discrepancy between the proposed technique with the laser interferometer (with an optical square) result was $0.6{\mu}rad$.

• 한국지능시스템학회논문지
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• 제19권3호
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• pp.408-414
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• 2009

UGV가 임무를 수행하기 위해서는 먼저 자신의 위치를 인식하는 것이 중요하며, 위치 인식을 위해 일반적으로 GPS나 INS 등 하나의 센서로 구성된 항법시스템을 이용한다. 그러나 GPS와 INS와 같은 센서들은 각각 단독으로 사용되기에는 제한사항을 가지고 있다. 즉 GPS는 정확한 위치정보의 제공이 가능하지만 기상과 환경에 의해 위치정보가 단절되며, INS는 독자적인 항법정보의 제공이 가능하지만 오차가 누적되어 정확한 위치추정이 어렵다는 문제점을 가지고 있다. 따라서 연속적이고 정확한 위치추정을 위해서는 센서 융합을 통한 복합 항법시스템이 필요하다. 따라서 본 논문에서는 GPS와 INS를 융합한 복합 항법시스템을 구성하기 위해 퍼지추론과 언센티드 파티클 필터를 이용한 UGV의 데이터 융합 및 위치추정 알고리즘을 제안한다. 퍼지추론은 GPS와 INS를 융합하는데 있어 수학적인 방법보다 더 간단하게 구현이 가능하며, 언센티드 파티클 필터는 오차보정에 탁월한 성능을 보여주는 비선형 추정 필터이다. 제안한 알고리즘의 성능을 비교분석하기 위해 실험을 실시하였으며, 실험 결과 제안한 알고리즘이 기존 알고리즘보다 연속적이고 정밀한 위치추정이 가능함을 입증하였다.

• 자동차안전학회지
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• 제14권3호
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• pp.71-76
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• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Journal of Advanced Marine Engineering and Technology
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• 제24권1호
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• pp.119-126
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• 2000

In constructing the positioning system based on a conventional dead-reckoning for a wheeled vehicle with pneumatic tires, the position estimation error is inevitable as changes of the radius of the wheels depend on live load and variable enviroment. Therefore, this paper proposes the positioning system which can estimate the error source i.e. the vehicle parameter errors, such as the right and left wheel radius error, using gyroscope and ultrasonic sensor and correct the parameter to reduce the dead-reckoned position estimation error. The extended Kalman filter was used as a method for the multisensor data fusion. The simulation to verify the effectiveness of the proposed positioning system is performed.

• Journal of Power Electronics
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• 제12권4호
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• pp.604-614
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• 2012

This paper presents a comparative study of position sensorless control schemes based on back-electromotive force (back-EMF) estimation in permanent magnet synchronous motors (PMSM). The characteristics of the estimated back-EMF signals are analyzed using various mathematical models of a PMSM. The transfer functions of the estimators, based on the extended EMF model in the rotor reference frame, are derived to show their similarity. They are then used for the analysis of the effects of both the motor parameter variations and the voltage errors due to inverter nonlinearity on the accuracy of the back-EMF estimation. The differences between a phase-locked-loop (PLL) type estimator and a Luenberger observer type estimator, generally used for extracting rotor speed and position information from estimated back-EMF signals, are also examined. An experimental study with a 250-W interior-permanent-magnet machine has been performed to validate the analyses.

• 전기학회논문지P
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• 제54권2호
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• 한국전자통신학회논문지
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• 제8권11호
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• pp.1681-1690
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• 2013

본 논문은 IPMSM(Interior Permanent Magnet Synchronous Motor)의 센서리스 운전을 위해 확장 칼만 필터를 기반으로 하는 속도와 위치 추정기의 설계방법을 제안한다. 제안된 방법은 상태 추정의 정밀도를 향상시키기 위해서 시스템 모델의 상태추정구간을 더욱 세분화하여 나누고, 세분화한 각 구간을 테일러급수 전개하여 일차항만 사용하여 추정하였다. 제안된 상태 추정기는 2차 확장칼만필터에 비해 사전추정의 연산의 양을 크게 하지 않고, 상태추정의 정밀도가 증가함을 시뮬레이션을 통해 보일 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.180-182
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• 2021

본 논문은 실내 환경에서 사용자를 대상으로 위치기반 서비스를 제공하기 위해 비콘을 이용해 사용자의 위치를 추정하는 방법을 제안한다. 저전력 비콘을 이용하여 위치를 추정하기 위해 비콘이 가지는 RSSI 값에 가우시안 필터를 적용하였고, 필터링한 RSSI 값을 통해 거리변환 함수를 구하여 삼변측량으로 태그 위치를 추정할 수 있게 구성하였다. 다수의 비콘이 설치된 실내 공간에서 3개의 비콘이 일정한 거리를 두고 있는 8곳에 대한 위치 추정 정밀도를 확인하였다. 그 결과 거리오차 0.242 표준편차 ±0.097를 가지는 사용자의 위치 추정이 가능함을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제4권1호
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• pp.62-67
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• 1998

Gimballed Inertial Navigation Systems(GINS) are sophisticated autonomous electro-mechanical systems which supply the position, velocity and attitude of the vehicle on which they are mounted. In order to maintain accuracy of outputs, the GINS are required to regularly calibrate senior errors. However, existing calibration methods take up a long time due to multiposition alignments needed to increase accuracy. A particular system formulation for calibration of a GINS is proposed to enhance system observability and thus to expedite calibration procedure. Performance of the proposed calibration method is compared with existing methods such as Schuler test and muliposition alignment. Simulation studies show the proposed system formulation associated with a suggested suboptimal filter is accurate as well as efficient in error identification essential to GINS calibration.