• International Journal of Internet, Broadcasting and Communication
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• 제10권4호
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• pp.70-74
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• 2018

In order to ensure the flow of goods available and more flexible, reduce labor costs, many factories and industrial zones around the world are gradually moving to use automated solutions. One of them is to use Automated guided vehicles (AGV). Currently, there are a line tracing method as an AGV operating method, and a method of estimating the current position of the AGV and matching with a factory map and knowing the moving direction of the AGV. In this paper, we propose ceiling Light and guided line based moving direction estimation algorithm using multi-camera on the AGV in smart factory that can operate stable AGV by compensating the disadvantages of existing AGV operation method. The proposed algorithm is able to estimate its position and direction using a general - purpose camera instead of a sensor. Based on this, it can correct its movement error and estimate its own movement path.

• 한국멀티미디어학회논문지
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• 제24권2호
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• pp.305-311
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• 2021

One of the highly reliable object tracking methods is to trace objects by associating objects detected by deep learning. The detected object is represented by a rectangular box. The box has information such as location and size. Since the tracker has motion information of the object in addition to the location and size, knowing additional information about the motion of the detected box can increase the reliability of object tracking. In this paper, we present a new method of reliably estimating the moving direction of the detected object in underground parking lot. First, the frame difference image is binarized for detecting motion energy, change due to the object motion. Then, a cumulative binary image is generated that shows how the motion energy changes over time. Next, the moving direction of the detected box is estimated from the accumulated image. We use a new cost function to accurately estimate the direction of movement of the detected box. The proposed method proves its performance through comparative experiments of the existing methods.

• 융합신호처리학회논문지
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• 제4권3호
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• pp.1-6
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• 2003

탱크나 경유자동차 등과 같이 지상에서 이동하는 차량들의 엔진소음은 광대역 특성을 갖고 또한 지형의 다양성 및 표적의 이동으로 인한 다양한 반사 등으로 변화가 심하기 때문에 탐지나 추적이 쉽지 않다 또한 전장 등과 같이 복잡한 환경에서는 배열안테나의 위치 선정 등의 어려움으로 앨리아싱이 일어날 수도 있다. 본 논문에서는 수동 배열 안테나의 성긴 배치로 인한 심각한 공간 앨리아싱 조건하에서 광대역 신호를 방사하는 이동체의 탐지 및 추적 문제에 대해서 연구하였다. 여기서 서브밴드 MUSIC 알고리즘에 근거한 고해상도의 방위각 추정 알고리즘을 개발하였다. 이 것은 공간 앨리아싱으로 인하여 표적의 방위각 추정 값이 변할 때에도 실제의 방위각을 추정할 수 있는 알고리즘이다 결과적으로 이 알고리즘이 성긴 안테나 배치로 인한 공간 앨리아싱 영향을 극복하고 위치 추정을 개선함을 보인다.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.12-16
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• 2007

In this paper, a new method is proposed for tracking the direction-of-arrival (DOA) of the wideband moving source incident on uniform linear array sensors. DOA is estimated by focusing transformation matrices. To update focusing matrices along with new data snap shots, we use the FAST (Fast Approximate Subspace Tracking) method. Present focusing matrices are constructed by previous signal and its orthogonal basis vectors as well as present signal and its orthogonal basis vectors, which are the left and right singular vectors of the inner product of two approximated matrices. Simulation results are shown to illustrate the performance of the proposed method.

• 제어로봇시스템학회논문지
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• 제17권3호
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.500-504
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• 2002

The purpose of this paper is to implement a guidance system for an object on the road. A watch camera equipped on the auto door recognizes the direction for the destination of an object, after that it determines whether opening or closing the door, and then the door is opened automatically, based on the decision. The motion of the moving object is approximated by using the technique of the image processing of tracking images and the affine model. The direction of the moving object is predicted from image information obtained by applying linear Kalman filter to the motion estimation in order to reduce the search region, the moving position, and the direction of the center of the object. Along with the guidance function, the system has the announcing function to the object. The experimental results confirm the veridity and applicability of the proposed system.

• 한국통신학회논문지
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• 제21권5호
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• pp.1109-1122
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• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.557-557
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• 2000

Tracking of the moving object, which is realized by the computer vision, is used for military and industrial fields. It is the application technique with imply complicated processing for understanding the input images. But, in these days, the most moving object tracking algorithms have many difficult problems. A typical problem is the increase of calculation time depending on target number. For this reason, there are many studies to solve real time processing problems and errors for background environmental change. In this paper, we used optical flow which is one of moving object tracking algorithms. It represents vector of the moving object. Optical flow estimation based on the regularization method depends on iteration method but it is very sensitive the noise. We proposed a new method using the Combinatorial Hough Transform (CHT) and Voting Accumulation in order to find optimal constraint lines. Also, we used the logical operation in order to release the operation time. The proposed method can easily and accurately extract the optical flow of moving object area and the moving information. We have simulated the proposed method using the test images. This images are included the noise. Experimental results show that the proposed method get better flow and estimate accurately the moving information.

• 대한의용생체공학회:의공학회지
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• 제15권4호
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• pp.455-464
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• 1994

The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMG signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements.

• 한국군사과학기술학회지
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• 제20권3호
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• pp.369-375
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• 2017

One of good DF(Direction Finding) methods is based on TDOA(Time Difference of Arrival) estimation when finding underwater moving target. For small DF error, high time resolution A/D(Analog-to-digital) conversion board and long baseline are needed. But the result of sea trial about close-range and high speed moving target, spatial correlation coefficient and appeared poor properties below 0.3 when hydrophone arrangement are separated over 6 ${\lambda}$ because of underwater fading channel. And we also find out that the distance between hydrophone should be under 4 ${\lambda}$ apart to take advantage of spatial correlation coefficient gain and performance of DF in underwater moving channel environments.