• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권2호
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• pp.140-146
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• 2013

In this paper, we describe a vision sensor-based driving algorithm for indoor automatic guided vehicles (AGVs) that facilitates a path tracking task using two mono cameras for navigation. One camera is mounted on vehicle to observe the environment and to detect markers in front of the vehicle. The other camera is attached so the view is perpendicular to the floor, which compensates for the distance between the wheels and markers. The angle and distance from the center of the two wheels to the center of marker are also obtained using these two cameras. We propose five movement patterns for AGVs to guarantee smooth performance during path tracking: starting, moving straight, pre-turning, left/right turning, and stopping. This driving algorithm based on two vision sensors gives greater flexibility to AGVs, including easy layout change, autonomy, and even economy. The algorithm was validated in an experiment using a two-wheeled mobile robot.

• Journal of Welding and Joining
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• 제17권6호
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• pp.90-99
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• 1999

Significant portion of the total manufacturing time for a pipe fabrication process is spent on the welding following primary machining and fit-up processes. To achieve a reliable weld bead appearance, automatic seam tracking and adaptive control to fill the groove are urgently needed. For the seam tracking in welding processes, the vision sensors have been successfully applied. However, the adaptive filling control of the multi-torches system for the appropriate welded area has not been implemented in the area of SAW(submerged arc welding) by now. The term adaptive control is often used to describe recent advances in welding process control by strictly this only applies to a system which is able to cope with dynamic changes in system performance. In welding applications, the term adaptive control may not imply the conventional control theory definition but may be used in the more descriptive sense to explain the need for the process to adapt to the changing welding conditions. This paper proposed various types of methodologies for obtaining a good bead appearance based on multi-torches welding system with the vision system in SAW. The methodologies for adaptive filling control used welding current/voltage, arc voltage/welding current/wire feed speed combination and welding speed by using vision sensor. It was shown that the algorithm for welding current/voltage combination and welding speed revealed sound weld bead appearance compared with that of voltage/current combination.

• 전기학회논문지
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• 제62권6호
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• pp.852-862
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• 2013

This paper proposes a target tracking control method for wheeled mobile robots with nonholonomic constraints by using a backstepping-like feedback linearization. For the target tracking, we apply a vision system to mobile robots to obtain the relative posture information between the mobile robot and the target. The robots do not use the sensors to obtain the velocity information in this paper and therefore assumed the unknown velocities of both mobile robot and target. Instead, the proposed method uses only the maximum velocity information of the mobile robot and target. First, the pseudo command for the forward linear velocity and the heading direction angle are designed based on the kinematics by using the obtained image information. Then, the actual control inputs are designed to make the actual forward linear velocity and the heading direction angle follow the pseudo commands. Through simulations and experiments for the mobile robot we have confirmed that the proposed control method is able to track target even when the velocity sensors are not used at all.

• 한국항공우주학회지
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• 제37권3호
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• pp.267-274
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• 2009

최근 무인 항공기(Unmanned Aerial Vehicle, UAV)는 다양한 임무수행이 가능한 무인 시스템이라는 점에서 크게 주목받고 있다. 특히 정찰, 추적 등의 임무는 영상을 이용하여 임무 수행이 이루어진다. 소형 무인 항공기의 경우 중량과 비용을 고려하여 단안 영상을 이용하는 임무 수행 연구가 활발하게 이루어지고 있다. 그러나 실제 지표면과 목표물이 고도 차이를 가지고 있어, 영상의 상대깊이를 고려하지 않은 3차원 거리는 임무 수행 시 오차 요인으로 작용 할 수 있다. 본 연구에서는 상대 깊이 추정을 위한 평균이동 알고리즘, 광류, 부분 공간법에 관하여 차례로 제시한다. 평균이동 알고리즘은 영상 내 목표물 추적과 관심영역을 결정하며 광류는 영상의 자기를 이용한 영상 이동 정보를 포함한다. 마지막으로 부분 공간법은 영상안의 움직임을 추정하며 각 영역의 상대깊이를 결정한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• 한국멀티미디어학회논문지
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• 제20권6호
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• pp.893-910
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• 2017

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권2호
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• pp.118-123
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• 2011

Video based object tracking normally deals with non-stationary image streams that change over time. Robust and real time moving object tracking is considered to be a problematic issue in computer vision. Multiple object tracking has many practical applications in scene analysis for automated surveillance. In this paper, we introduce a specified object tracking based particle filter used in an environment of multiple moving objects. A differential image region based tracking method for the detection of multiple moving objects is used. In order to ensure accurate object detection in an unconstrained environment, a background image update method is used. In addition, there exist problems in tracking a particular object through a video sequence, which cannot rely only on image processing techniques. For this, a probabilistic framework is used. Our proposed particle filter has been proved to be robust in dealing with nonlinear and non-Gaussian problems. The particle filter provides a robust object tracking framework under ambiguity conditions and greatly improves the estimation accuracy for complicated tracking problems.

• 건설관리
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• 제14권5호
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• pp.32-35
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• 2013

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.93-104
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• 2005

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.515-526
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• 2003

Tutorial contents of kinematics and dynamics of a wheeled drive mobile robot are presented. Based on the dynamic model, simulation studies of position tracking of a mobile robot are performed. The control structure of several position control algorithms using visual feedback are proposed and their performances are compared. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position control schemes are proposed. Experiments are conducted and the results show the performance of the vision based neural network control scheme fumed out to be the best among several proposed schemes.