• Title/Summary/Keyword: Angular Filter

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Implementation of Electronic Personal Dosimeter Using Silicon PIN Photodiode (실리콘 핀 포토다이오드를 이용한 능동형 방사선 피폭 전자선량계의 구현)

  • 이운근;백광렬;권석근
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.4
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    • pp.296-303
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    • 2003
  • A personal portable type electronic dosimeter using silicon PIN photodiode and small GM tube is recently attracting much attention due to its advantages such as an immediate indication function of dose and dose rate, alerting function, and efficient management of radiation exposure history and dose data. We designed and manufactured a semiconductor radiation detector aimed to directly measure X-ray and v-ray irradiated in silicon PIN photodiode, without using high-priced scintillation materials. Using this semiconductor radiation detector, we developed an active electronic dosimeter, which measures the exposure dose using pulse counting method. In this case, it has a shortcoming of over-evaluating the dose that shows the difference between the dose measured with electronic dosimeter and the dose exposed to the human body in a low energy area. We proposed an energy compensation filter and developed a dose conversion algorithm to make both doses indicated on the detector and exposed to the human body proportional to each other, thus enabling a high-precision dose measurement. In order to prove its reliability in conducting personal dose measurement, crucial for protecting against radiation, the implemented electronic dosimeter was evaluated to successfully meet the IEC's criteria, as the KAERI (Korea Atomic Energy Research Institute) conducted test on dose indication accuracy, and linearity, energy and angular dependences.

Expanded Exit-Pupil Holographic Head-Mounted Display With High-Speed Digital Micromirror Device

  • Kim, Mugeon;Lim, Sungjin;Choi, Geunseop;Kim, Youngmin;Kim, Hwi;Hahn, Joonku
    • ETRI Journal
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    • v.40 no.3
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    • pp.366-375
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    • 2018
  • Recently, techniques involving head-mounted displays (HMDs) have attracted much attention from academia and industry owing to the increased demand for virtual reality and augmented reality applications. Because HMDs are positioned near to users' eyes, it is important to solve the accommodation-vergence conflict problem to prevent dizziness. Therefore, holography is considered ideal for implementing HMDs. However, within the Nyquist region, the accommodation effect is limited by the space-bandwidth-product of the signal, which is determined by the sampling number of spatial light modulators. In addition, information about the angular spectrum is duplicated over the Fourier domain, and it is necessary to filter out the redundancy. The size of the exit-pupil of the HMD is limited by the Nyquist sampling theory. We newly propose a holographic HMD with an expanded exit-pupil over the Nyquist region by using the time-multiplexing method, and the accommodation effect is enhanced. We realize time-multiplexing by synchronizing a high-speed digital micromirror device and a liquid-crystal shutter array. We also demonstrate the accommodation effect experimentally.

Tracking and Capturing a Moving Object Using Active Camera Mounted on a Mobile Robot (이동로봇에 장착된 능동 카메라를 이용한 이동물체의 추적과 포획)

  • Park, Jin-U;Park, Jae-Han;Yun, Gyeong-Sik;Lee, Jang-Myeong
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.9
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    • pp.741-748
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    • 2001
  • In this paper, we propose a method of tracking and capturing a moving object by a mobile robot. The position of the moving object is acquired from the relation through color-based image information from a 2-DOF active camera mounted on the mobile robot. The direction and rotational angular velocity of the moving object are estimated using a state estimator. A Kalman fiber is used as the state estimator for taking characteristics of robustness against noises and uncertainties included in the input data. After estimating the trajectory of the moving object, we decide on the optimal trajectory and plan the motion of the mobile robot to capture the target object within the shortest distance and time. The effectiveness of the proposed method is demonstrated by the simulations and experiments.

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Complex Vector Current Control of Grid Connected Inverter Robust for Inductance Variation (인덕턴스 변화에 강인한 계통연계형 인버터의 복소 벡터 전류제어기)

  • Lee, Taejin;Jo, Jongmin;Shin, Changhoon;Cha, Hanju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.10
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    • pp.1648-1654
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    • 2016
  • This paper analyzes complex vector current control for the enhanced cross-coupling compensation in accordance with parameter variation in grid-connected inverter system, and verifies through simulation and experiment. Complex vector current control is performed in the synchronous reference frame through d-q transformation. It generates cross-coupling components with rotating nominal angular frequency. In general, cross-coupling elements are compensated by decoupling terms added to output of conventional decoupling PI controller. But, it is impossible to compensate them perfectly which transient response is especially deteriorated such as large overshoot and slow tracking, when variation of grid impedance or measurement error occurs. However, complex vector current control can improve stability and response characteristic of current control regardless of the situation as before. Decoupling controller and complex vector controller are represented through complex forms, and these controllers are analyzed by using frequency response in s-domain, respectively. It is verified that complex vector controller has more superior response characteristic than decoupling controller through MATALB, PSIM and experimental in 5kW grid-connected inverter when L filter parameter is varied from 1.1mH to increase double, 2.2mH.

A Study on Tracking Control of an Industrial Overhead Crane Using Sliding Mode Controller (슬라이딩모드 제어기를 이용한 산업용 천정크레인의 추종제어에 관한 연구)

  • Park, Byung-Suk;Yoon, Ji-Sup;Kang, E-Sok
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.11
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    • pp.1022-1032
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    • 2000
  • We propose a sliding mode controller tracking the states of a time-varying reference model. The reference model generates the desired trajectories of the states, and the sliding mode controller regulates robustly the errors between the desired states and the measured states. We apply this controller to the overhead crane. Its reference model generates the trajectories of the damped-out swing angle and the swing angular velocity to suppress the swinging motion caused by the acceleration and the deceleration of crane transportation. Also, this model generates the desired trajectories of the position and velocity of the crane. The crane model is identified from the experimental data using an orthogonal function. Kalman filtering is applied to estimate the crane states. The designed controller is simulated on a computer and is tested through a 2-ton industrial overhead crane using the vector-controlled servo motor system. It is verified that, from the simulated and experimental results, the sliding mode controller tracking a time-varying reference model works well.

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Moving Object Following by a Mobile Robot using a Single Curvature Trajectory and Kalman Filters (단일곡률궤적과 칼만필터를 이용한 이동로봇의 동적물체 추종)

  • Lim, Hyun-Seop;Lee, Dong-Hyuk;Lee, Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.7
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    • pp.599-604
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    • 2013
  • Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

Performance Improvement of an INS by using a Magnetometer with Pedestrian Dynamic Constraints

  • Woyano, Feyissa;Park, Aangjoon;Lee, Soyeon
    • IEIE Transactions on Smart Processing and Computing
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    • v.6 no.1
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    • pp.1-9
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    • 2017
  • This paper proposes to improve the performance of a strap down inertial navigation system using a foot-mounted low-cost inertial measurement unit/magnetometer by configuring an attitude and heading reference system. To track position accurately and for attitude estimations, considering different dynamic constraints, magnetic measurement and a zero velocity update technique is used. A conventional strap down method based on integrating angular rate to determine attitude will inevitably induce long-term drift, while magnetometers are subject to short-term orientation errors. To eliminate this accumulative error, and thus, use the navigation system for a long-duration mission, a hybrid configuration by integrating a miniature micro electromechanical system (MEMS)-based attitude and heading detector with the conventional navigation system is proposed in this paper. The attitude and heading detector is composed of three-axis MEMS accelerometers and three-axis MEMS magnetometers. With an absolute algorithm based on gravity and Earth's magnetic field, rather than an integral algorithm, the attitude detector can obtain an absolute attitude and heading estimation without drift errors, so it can be used to adjust the attitude and orientation of the strap down system. Finally, we verify (by both formula analysis and from test results) that the accumulative errors are effectively eliminated via this hybrid scheme.

Moving Object Trajectory based on Kohenen Network for Efficient Navigation of Mobile Robot

  • Jin, Tae-Seok
    • Journal of information and communication convergence engineering
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    • v.7 no.2
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    • pp.119-124
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    • 2009
  • In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

A Study on Kohenen Network based on Path Determination for Efficient Moving Trajectory on Mobile Robot

  • Jin, Tae-Seok;Tack, HanHo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.2
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    • pp.101-106
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    • 2010
  • We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

PID and Adaptive Controllers for a Transportation Mobile Robot with Fork-Type Lifter

  • Nguyen, Van Vui;Tran, Huu Luat;Kim, Yong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.3
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    • pp.216-223
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    • 2016
  • This paper proposes a new controller design method for a fork-type lifter (FTL) of a transportation mobile robot. The transportation robot needs to pick up a package from a stack on a storage shelf and move on by a planned path in a logistics center environment. The position of the storage shelf is recognized by reading a QR code on the floor, and using this position, the robot can move to reach the storage shelf and pick up the package. PID controllers and an adaptive controller are designed to control the velocity of two wheels and the position of the FTL. An adaptive controller for the lifter is designed to elevate up and down on a slideway to the correct height position of the package on the stack of the storage shelf. The simulation results show that the PID controllers can respond smoothly to the desired angular velocity and the adaptive controller can adapt quickly and correctly to the desired height.