• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1908-1913
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• 2010

In this paper, a robust variable structure tracking controller is designed for the mixed tracking control of highly nonlinear rigid robot manipulators for the first time. The mixed control problem under consideration is extended from the basic tracking problem, with the different initial condition of both the planned trajectory and link of robots. This control problem in robotics is not addressed to until now. The tracking accuracy to the sliding trajectory after reaching is analyzed. The stability of the closed loop system is investigated in detail in Theorem 2. The results of Theorem 2 provide the stable condition for control gains. Combing the results of Theorem 1 and Theorem 2 gives rise to possibility of designing the improved variable structure tracking controller to guarantee the tracking error from the determined sliding trajectory within the prescribed accuracy after reaching. The usefulness of the algorithm has been demonstrated through simulation studies on the mixed tracking control of a two.link robot under parameter uncertainties and payload variations.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.408-408
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• 2000

A parabolic dish concentrator used in a high temperature application of solar energy tracks the sun's movement by two axis sun tracking system. In such a system, sun tracking performance affects the system efficiency directly. Generally the higher the tracking accuracy is, the better the system performance is. A large number of parabolic dish type concentrators has been developed and implemented in the world. However none of them clearly provided a qualitative method of how the accuracy of the sun tracking system can be evaluated. The work presented here is the evaluation of sun tracking performance of parabolic dish concentrator, which follows the sun's movement by the sensor, using computer vision system. We install a camera on the parabolic dish concentrator. While the concentrator follows the sun, sun's images are captured continuously. Then the performance of sun tracking system was evaluated by analyzing the variation of the position of the sun in the images.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.143-148
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• 2001

A lot of robot trajectory tracking methods are proposed to enhance the tracking error, but irregular tracking errors are always accompanied and very hard to reduce it. Up to now, these irregular tracking errors are reduced by introducing more complicated control algorithms. But, it is intuitively obvious to reduce only the big errors selectively in the irregular ones for the better performance instead of using more complicated control algorithms. By the characteristics of the robot, big tracking errors of the end-effector are generated mostly due to the fast moving of joint. So, in this paper, we introduce a new method which reduce the big tracking errors by clippings the joint velocity with the constraint of given path. Using this method, desired trajectory tracking is obtained within the far reduced error bound. Also, this method is successfully applied to generate the path-constrained error reducing trajectories for 2-axis SCARA type robot.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.270-277
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• 1999

This paper deals with the maneuver detection and target tracking problem in uncertain parameter systems using a robust{{{{ { H}_{ } }}}} FIR filter to improve the unacceptable tracking performance due to the parametr uncertainty. The tracking filter used in the current paper is based on the robust{{{{ { H}_{ } }}}} FIR filter proposed by Kwon et al. [1,2] to estimate the state signal in uncertain systems with parameter uncertainty, and the basic scheme of the proposed method is the input estimation approach. Tracking performance of the maneuver detection and target tracking method proposed is compared with other techniques, Bogler allgorithm [4] and FIR tracking filter [2], via some simulations to examplify the good tracking performance of the proposed method over other techniques.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.73-83
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• 2022

Visual object tracking can be utilized in various applications and has attracted considerable attention in the field of computer vision. Visual object tracking technology is classified in various ways based on the number of tracking objects and the methodologies employed for tracking algorithms. This report briefly introduces the visual object tracking challenge that contributes to the development of single object tracking technology. Furthermore, we review ten Siamese network-based algorithms that have attracted attention, owing to their high tracking speed (despite the use of neural networks). In addition, we discuss the prospects of the Siamese network-based object tracking algorithms.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.80-88
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• 2023

RGB-thermal (RGB-T) tracking using unmanned aerial vehicles (UAVs) involves challenges with regards to the similarity of objects, occlusion, fast motion, and motion blur, among other issues. In this study, we propose dynamic tracking aggregation (DTA) as a unified framework to perform object detection and data association. The proposed approach obtains fused features based a transformer model and an L1-norm strategy. To link the current frame with recent information, a dynamically updated embedding called dynamic tracking identification (DTID) is used to model the iterative tracking process. For object association, we designed a long short-term tracking aggregation module for dynamic feature propagation to match spatial and temporal embeddings. DTA achieved a highly competitive performance in an experimental evaluation on public benchmark datasets.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1134-1139
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• 2003

Tracking is a fundamental technique which is able to be applied to gesture recognition, visual surveillance, tangible agent and so forth. Especially, multiple object tracking has been extensively studied in recent years in order to perform many and more complicated tasks. In this paper, we propose a new approach of multiple object tracking which is based on discrete event. We call this system the DEMOT (Discrete Event based Multiple Object Tracking). This approach is based on the fact that a multiple object tracking can have just four situations - initiation, continuation, termination, and overlapping. Here, initiation, continuation, termination, and overlapping constitute a primary event set and this is based on the change of the number of extracted objects between a previous frame and a current frame. This system reduces computational costs and holds down the identity of all targets. We make experiments for this system with respect to the number of targets, each event, and processing period. We describe experimental results that show the successful multiple object tracking by using our approach.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.133-138
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• 2016

This paper describes the track initiation and target-tracking filter for ship tracking in a marine environment by using Light Detection And Ranging (LiDAR). LiDAR with three-dimensional scanning capability is more useful for target tracking in the short to medium range compared to RADAR. LiDAR has rotating multi-beams that return point clouds reflected from targets. Through preprocessing the cluster of the point cloud, the center point can be obtained from the cloud. Target tracking is carried out by using the center points of targets. The track of the target is initiated by investigating the normalized distance between the center points and connecting the points. The regular track obtained from the track initiation can be maintained by the target-tracking filter, which is commonly used in radar target tracking. The target-tracking filter is constructed to track a maneuvering target in a cluttered environment. The target-tracking algorithm including track initiation is experimentally evaluated in a sea-trial test with several boats.

• Journal of Korea Multimedia Society
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• v.20 no.6
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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.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.207-214
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• 2020

In this paper, we implement linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) instead of conventional extended Kalman filter based vector tracking loop (EKF-VTL). The LQG-VTL can improve the performance compared to the EKF-VTL by generating optimal control input at a specific performance index. Performance analysis is conducted through two factors, frequency thermal noise and frequency dynamic stress error, which determine total frequency tracking error. We derive the thermal noise and the dynamic stress error formula in the LQG-VTL. From frequency tracking error analysis, we can determine control gain matrix in the LQG controller and show that the frequency tracking error of the LQG-VTL is lower than that of the EKF-VTL in all C/N0 ranges. The simulation results show that the LQG-VTL improves performance by 30% in Doppler tracking, so the LQG-VTL can extend pre-integration time longer and track weaker signals than the EKF-VTL. Therefore, the LQG-VTL algorithm is more robust than the EKF-VTL in weak signal environments.