• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.9
• /
• pp.1827-1833
• /
• 2009

This paper deals with the trajectory tracking control of wheeled mobile robots with input constraint. The proposed method converts the trajectory tracking problem to the system stability problem using the control inputs composed of feedforward and feedback terms, and then, by using Taylor series, nonlinear terms in origin system are transformed into polynomial equations. The composed system model can make it possible to obtain the control inputs using numerical tool named as SOSTOOL. From the simulation results, the mobile robot can track the reference trajectory well and can have faster convergence rate of the trajectory errors than the existing nonlinear control method. By using the proposed method, we can easily obtain the control input for nonlinear systems with input constraint.

• Proceedings of the KIEE Conference
• /
• 2006.07c
• /
• pp.1467-1468
• /
• 2006

본 논문에서는 현재 운용되고 있는 낙뢰탐지 시스템들과는 다른 측위방식인 TDOA(Time Difference of Arrival)방법을 사용한 3차원 낙뢰 탐지 및 추적 시스템을 제안한다. TDOA방식은 낙뢰와 수신국사이의 도달시간을 측정하여 두 수신국간의 시간차가 일정한 쌍곡선을 얻고 이들 쌍곡선의 교점을 이용해 낙뢰의 위치를 결정하는 방법이다. 이 시스템을 이용하여 위치정확도가 수 미터인 3차원 낙뢰 방전 궤적을 얻을 수 있다. 시스템의 구현을 위해서 먼저 낙뢰의 신호를 저장해야 하는데, 광대역의 낙뢰신호를 저장하기 위해서는 고속의 디지타이저가 필요하다. 그러나 디지타이저와 프로세서간의 인터페이스의 한계로 연속적으로 이를 저장하는 것은 어려우며, 이러한 신호 저장의 문제점을 해결하기 위해서 낙뢰 신호 저장 시스템이 필요하다. 본 논문에서는 낙뢰의 메커니즘과 광대역 낙뢰신호 검출기법을 설명하고, 구현한 낙뢰 신호 저장 시스템을 소개한다.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.1 s.232
• /
• pp.88-95
• /
• 2005

This paper presents a design scheme of model reference adaptive control incorporating a Neural Network for a pneumatic servo system. The parameters of discrete-time model of plant are estimated by using the recursive least square method. Neural Network is utilized in order to compensate the nonlinear nature of plant such as compressibility of air and frictions present in cylinder. The experiment of a trajectory tracking control using the proposed control scheme has been performed and its effectiveness has been proved by comparing with the results of a model reference adaptive control.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.472-473
• /
• 2013

The growth in number and efficiency of smart devices such as GPS enabled smart phones and PDAs present an unparalleled opportunity for diverse areas of life. However extraction of GPS traces for provision of services demand a huge storage space as well as computation overhead. This is a challenging task especially for the applications which provide runtime services. In this paper we provide a simplified model to extract GPS traces of moving objects at runtime. Road segment partitioning and measure of deviation in angle of trajectory path is incorporated to identify the significant data points. The number of these data points is minimized by our proposed approach in an efficient manner to overwhelm the storage and computation overhead. Further, the competent reconstruction of complete itinerary based on gathered data, is also ensured by proposed method.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.6
• /
• pp.355-365
• /
• 2022

This paper addresses the problem of real-time tracking a high-speed ballistic target. Particle filters can be considered to overcome the nonlinearity in motion and measurement models in the ballistic target. However, it is difficult to apply particle filters to real-time systems because particle filters generally require much computation time. This paper proposes an accelerated particle filter using graphics processing unit (GPU) for real-time ballistic target tracking. The real-time performance of the proposed method was tested and analyzed on a widely-used embedded system. The comparison results with the conventional particle filter on CPU (central processing unit) showed that the proposed method improved the real-time performance by reducing computation time significantly.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.736-739
• /
• 2010

본 논문에서는 배경영상과 교차로 내의 신호등의 주기를 이용한 교차로 교통 사고 감지 방법을 제안한다. 교차로 내의 객체의 움직임 궤적 정보, 객체의 움직임 정보에 기반한 배경영상 생성과 교차로 신호등 주기를 이용하는 사고 감지 방법으로 구성된다. 환경적인 잡음과 카메라의 잡음을 효과적으로 제거하고 객체를 개별적으로 추적하지 않고 사고를 감지 할 수 있는 알고리즘을 개발하였다. 제안한 알고리즘의 성능을 알아보기 위하여 교차로에 설치된 DVR을 통해 다양한 환경의 사고영상을 저장하여 실험한 결과 모든 동영상에서 사고를 감지하였다.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.3
• /
• pp.177-186
• /
• 2012

In this paper, we propose a real-time approach for detecting and tracking a hand region by analyzing depth images. We build a hand model in advance. The model has the shape information of a hand. The detecting process extracts out moving areas in an image, which are possibly caused by moving a hand in front of a camera. The moving areas can be identified by analyzing accumulated difference images and applying the region growing technique. The extracted moving areas are compared against a hand model to get justified as a hand region. The tracking process keeps the track of center points of hand regions of successive frames. For this purpose, it involves three steps. The first step is to determine a seed point that is the closest point to the center point of a previous frame. The second step is to perform region growing to form a candidate region of a hand. The third step is to determine the center point of a hand to be tracked. This point is searched by the mean-shift algorithm within a confined area whose size varies adaptively according to the depth information. To verify the effectiveness of our approach, we have evaluated the performance of our approach while changing the shape and position of a hand as well as the velocity of hand movement.

• Journal of Korea Multimedia Society
• /
• v.16 no.6
• /
• pp.746-755
• /
• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.

• The Journal of Korean Association of Computer Education
• /
• v.15 no.3
• /
• pp.71-80
• /
• 2012

The purpose of this study is to find out the changing trajectory of online game use as the development of early adolescences. It is also to explore whether the self-control has a current and a lag effect on the game use while development of students. We found these results: (a) There is a statically significant individual variability in initial levels and rates of change in online game use over time. The change of trajectory is declined. (b) Boys also have higher rate of the change in using game than girls over time. (c) Both initial state and changing rate of online game use affects negatively the academic achievement. (d) Current effect always supports, but lag effect does not support except the period from last elementary school grade to middle school grade as explanations for the developmental relation between self-control and online game use in young adolescents.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.4
• /
• pp.698-707
• /
• 2017

This paper deals with predictive control methods of mobile robots for reference trajectory tracking control. Predictive control methods using predictive model are known as effective schemes that minimize the future errors between the reference trajectories and system states; however, the amount of real-time computation for the predictive control are huge so that their applications were limited to slow dynamic systems such as chemical processing plants. Lately with high computing power due to advanced computer technologies, the predictive control methods have been applied to fast systems such as mobile robots. These predictive controllers have some control parameters related to control performance. But these parameters have not been optimized. In this paper we employed the genetic algorithm to optimize the control parameters of the predictive controller for mobile robots. The improved performances of the proposed control method are demonstrated by the computer simulation studies.