• 한국인터넷방송통신학회논문지
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• 제23권2호
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• pp.113-118
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• 2023

실내에서의 위치 추정을 위한 WiFi fingerprint 방식은 기존의 인프라를 이용하며 절대 좌표를 추정하는 장점이 있어 많은 연구가 진행되고 있다. 기존의 연구에서는 주로 위치 추정 알고리즘에 대한 연구에 집중되었지만 정확도를 개선하는 것이 한계에 도달했다. 그러나 스마트폰과 같은 무선랜 수신기에서 전파의 수신 감도보다 작은 신호는 측정이 불가하므로 이 값들을 처리하는 방법에 따라서 위치 추정 오차가 달라진다. 본 논문에서는 측정된 무선랜 공유기의 수신 신호 데이터를 다양한 방식으로 사전 처리하여 기존의 알고리즘에 적용함으로써 위치 추정 정확도를 높이는 방법을 제안하였고, 크게 향상된 정확도를 얻을 수 있었다. 또한 사전 처리된 데이터를 KNN 방식과 CNN 방식에 적용하여 그 성능을 비교하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.1934-1935
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• 2011

In order for a service robot to perform several tasks, basically autonomous navigation technique such as localization, mapping, and path planning is required. The localization (estimation robot's pose) is fundamental ability for service robot to navigate autonomously. In this paper, we propose a new system for point pattern matching based visual global localization using spot lightings in ceiling. The proposed algorithm us suitable for system that demands high accuracy and fast update rate such a guide robot in the exhibition. A single camera looking upward direction (called ceiling vision system) is mounted on the head of the mobile robot and image features such as lightings are detected and tracked through the image sequence. For detecting more spot lightings, we choose wide FOV lens, and inevitably there is serious image distortion. But by applying correction calculation only for the position of spot lightings not whole image pixels, we can decrease the processing time. And then using point pattern matching and least square estimation, finally we can get the precise position and orientation of the mobile robot. Experimental results demonstrate the accuracy and update rate of the proposed algorithm in real environments.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.337-340
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• 2011

신호원으로부터 발생하는 전파를 이격된 다중센서에서 수신하여 신호원의 위치를 추정하는 시스템에서는 신호원의 위치와 센서들의 위치에 따라 위치추정 정확도가 저하되는 현상이 나타난다. 이러한 현상을 GDOP 효과라 하며, 이러한 효과를 최소화하여 위치탐지정확도 성능을 향상시키기 위한 방법에 대해 연구가 필요하다. 본 논문에서는 이격 배치된 센서들의 방위(AOA; Angle of Arrival) 정보를 이용하여 GDOP 효과의 발생 가능성을 추정하고, 위치 추정에서 오차 요인이 되는 센서를 제거하여 GDOP 효과로 인한 성능 저하를 최소화하는 방법에 관한 연구 결과를 서술하겠다.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• 로봇학회논문지
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• 제2권3호
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• pp.255-261
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• 2007

We propose a optimal fusion method for localization of multiple robots utilizing correlation between GPS on each robot in common workspace. Each mobile robot in group collects position data from each odometer and GPS receiver and shares the position data with other robots. Then each robot utilizes position data of other robot for obtaining more precise estimation of own position. Because GPS data errors in common workspace have a close correlation, they contribute to improve localization accuracy of all robots in group. In this paper, we simulate proposed optimal fusion method of odometer and GPS through virtual robots and position data.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.240-248
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• 2009

An approach to control the position for an interior permanent magnet synchronous motor (IPMSM) based on an adaptive integral binary observer is described. The binary controller with a binary observer is composed of a main loop regulator and an auxiliary loop regulator. One of its key features is that it alleviates chatter in the constant boundary layer. However, steady state estimation accuracy and robustness are dependent upon the thickness of the constant boundary layer. In order to improve the steady state performance of the binary observer and eliminate the chattering problem of the constant boundary layer, a new binary observer is formed by adding extra integral dynamics to the existing switching hyperplane equation. Also, the proposed adaptive integral binary observer applies an adaptive scheme because the parameters of the dynamic equations such as the machine inertia and the viscosity friction coefficient are not well known. Furthermore, these values can typically be easily changed during normal operation. However, the proposed observer can overcome the problems caused by using the dynamic equations, and the rotor position estimation is constructed by integrating the rotor speed estimated with a Lyapunov function. Experimental results obtained using the proposed algorithm are presented to demonstrate the effectiveness of the approach.

• Journal of Power Electronics
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• 제10권5호
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• pp.485-490
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• 2010

Sensorless control methods are generally used in motor control for home-appliances because of the material cost and manufactureing standard restrictions. The current model-based control algorithm is mainly used for PMSM sensorless control in the home-appliance industry. In this control method, the rotor position is estimated by using the d-axis and q-axis current errors between the real system and a motor model of the position estimator. As a result, the accuracy of the motor model parameters are critical in this control method. A mismatch of the PMSM parameters affects the speed and torque in low speed, steadystate responses. Rotor position errors are mainly caused by a mismatch of the stator resistance. In this paper, a stator resistance compensation algorithm is proposed to improve sensorless control performance. This algorithm is easy to implement and does not require a modification of the motor model or any special interruptions of the controller. The effectiveness of the proposed algorithm is verified through experimental results.

• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1139-1145
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• 2008

A robust position sensing system is proposed in this paper for a ubiquitous mobile robot which moves indoors as well as outdoors. The Differential GPS (DGPS) which has a position estimation error of less than 5 m is a general solution when the mobile robot is moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is reliable as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference coordinates and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. Using the database, the approaching status of the mobile robot from indoor to outdoor or vice versa has been checked and the switching conditions are prepared before the mobile robot actually moves out or moves into the door. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified and demonstrated through the real experiments using a mobile robot prepared for this research.

• 전기학회논문지
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• 제68권3호
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• pp.430-438
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• 2019

For a pump or a compressor motor, a high periodic load torque variation is induced by the mechanical works, and it causes system vibration and noise. To minimize these problems, load torque compensation method, injecting periodic torque current, could be utilized. However, with the sensorless control method, which is usually utilized in the pump and compressor for low cost, the periodic torque current degrades the accuracy of the rotor position estimation owing to the inductance variation. This paper analyzes the rotor position and speed estimation error of sensorless control method with constant motor parameters under period loading. Assuming the constant speed by the accurate load torque compensation, the speed error equation is derived in frequency domain with inductance depending on the stator current. Further, it is also shown that the rotor position error could be minimized by compensating the inductance variation. The simulation and experimental results verify that the derived speed error model and the validity of the inductance compensation method.