• Journal of Multimedia Information System
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• 제6권4호
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• pp.329-332
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• 2019

Recently, smart lighting systems are the combination between sensors and lights. These systems turn on/off and adjust the brightness of lights based on the motion of object and the brightness of environment. These systems are often applied in places such as buildings, rooms, garages and parking lot. However, these lighting systems are controlled by lighting sensors, motion sensors based on illumination environment and motion detection. In this paper, we propose an automatic lighting control system using one single camera for buildings, rooms and garages. The proposed system is one integration the results of digital image processing as motion detection, hand gesture detection to control and dim the lighting system. The experimental results showed that the proposed system work very well and could consider to apply for automatic lighting spaces.

• 전기전자학회논문지
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• 제18권4호
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• pp.612-619
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• 2014

본 논문에서는 움직임 감지를 사용하여 영상 해상도를 자동 제어하는 실시간 다중 카메라 영상 감시 시스템을 구현하였다. 평상시에는 4개 채널의 영상을 QVGA급으로 취득한 후 하나의 VGA급 영상으로 통합하여 전송한다. 움직임이 포착되는 경우에는 해당 채널의 영상을 자동으로 확대하여 VGA급으로 취득한 후 나머지 3개 채널의 영상을 QQVGA급으로 줄여서 오버레이한다. 이를 통하여 모든 채널의 영상을 놓치지 않으면서도 전송 대역폭을 늘리지 않고 움직임이 포착된 채널을 확대하여 감시할 수 있다. 0.18 um 공정에서 합성한 최대 동작 주파수는 110 MHz로서 이론상으로 4개의 HD급 카메라를 지원할 수 있다.

• 한국해양공학회지
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• 제36권1호
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• pp.50-60
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• 2022

The deep ocean engineering basin (DOEB) of the Korea Research Institute of Ship and Ocean Engineering (KRISO) is equipped with an extreme-environment reproduction facility that can analyze the motion characteristics of offshore structures and ships. In recent years, there have been requirements for a wide range of six-degree-of-freedom (6-DOF) motion measurements for performing maneuvering tests and free-running tests of target objects (offshore structures or ships). This study introduces the process of developing a wide-area motion measurement technology by incorporating the auto-tracking technology of the towing carriage system to overcome the existing 6-DOF motion measurement limitation. To realize a wide range of motion measurements, the automatic tracking control system of the towing carriage in the DOEB was designed as a speed control method. To verify the control performance, the characteristics of the towing carriage according to the variation in control gain were analyzed. Finally, a wide range of motions was tested using a model test object (a remotely operated vehicle (ROV)), and the wide-area motion measurement technology was implemented using an automatic tracking control system for a towing carriage.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.89-94
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• 1994

This paper presents an impact control algorithm for reducing the potentially damaging effects by interation of redundant manipulators with their environments. In the. proposed control algorithm, the redundancy is resolved at the torque level by locally minimizing joint torque, subject to tire operational space dynamic formulation which maps tire joint torque set into the operational forces. For a given pre-impact velocity of the manipulator, the proposed approach is on generating joint space trajectories throughout the motion near the contact which instantaneously minimize the impulsive force which is a scalar function of manipulator's configurations. This is done by using the null space dynamics which does not affect the motion of an end-effector. The comparative evaluation of the proposed algorithm with a local torque optimization algorithm without reducing impact is performed by computer simulation. The simulation results illustrate the effectiveness of the algorithm in reducing both the effects of impact and large torque requirements.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.163-169
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• 2021

In this paper, we implemented a deep learning-based automatic object tracking and handy motion control drone system and analyzed the performance of the proposed system. The drone system automatically detects and tracks targets by analyzing images obtained from the drone's camera using deep learning algorithms, consisting of the YOLO, the MobileNet, and the deepSORT. Such deep learning-based detection and tracking algorithms have both higher target detection accuracy and processing speed than the conventional color-based algorithm, the CAMShift. In addition, in order to facilitate the drone control by hand from the ground control station, we classified handy motions and generated flight control commands through motion recognition using the YOLO algorithm. It was confirmed that such a deep learning-based target tracking and drone handy motion control system stably track the target and can easily control the drone.

• 전기학회논문지
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• 제59권3호
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• pp.645-650
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• 2010

In this paper we present the Bimodal-tram simulator using the PXI embedded real-time controllers. The Bimodal-tram is developed in KRRI (Korea Railroad Research Institute). The vehicle can be automatically operated by navigation control system (NCS). For the automatic driving, the vehicle lanes will be marked with permanent magnets that are placed in the ground. The vehicle is controlled by NCS. NCS governs the manual mode and automatic mode driving. The simulator is designed by an identical conception with the real control condition. The dynamic motion of vehicle is simulated by the nonlinear dynamic model. The control computer calculates the control values. The signal interface is linked by CAN communication. The simulation is processed by real-time base. The test driver can see the graphic motion of vehicle and can operate the steering wheel, gas and brake pedal to control direction and velocity of vehicle during the simulation. At present, the simulator is only operated by manual mode. The automatic mode will be linked after the control algorithm is finished. We will use the simulator to develop the control algorithm in the automatic mode. This paper shows the simulator designed for Bimodal-tram using real-time based controller. The results of the test using the simulator are presented and discussed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.264-268
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• 1987

This paper is concerned on kinematic analysis and simulation of an automatic feeding mechanism subjected by the motion of a curvilinear inverse can. The curvilinear cam is rotated by positioning a translating roller and the automatic feeding mechanism is moved to the sliding position by the motion of a campin fixed on the curvilinear cam. The curvilinear cam consists of two arcs of circles and two straight lines. The modular approach is used for the kinematic analysis of the feeding mechanism. As the first part of the paper for the motion simulation of the cam-feeding system, this paper discusses the algorithm to simulate the motion of the cam-feeding mechanism. The second part of the paper presents the state-of-art for the graphics-oriented CAD technique,

• Journal of Ship and Ocean Technology
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• 제6권1호
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• pp.16-26
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• 2002

In this paper, a motion identification method using neural networks is applied to automatic ship berthing to overcome disturbance effects. Motion identification is used to estimate the effect of environmental disturbance. Two rule-based algorithms have been developed to over-come disturbance. The first rule based-algorithm was designed to overcome lateral disturbance when a ship's lateral speed is affected by it. The second rule-based algorithm was also designed to overcome longitudinal disturbance when a ship's angular velocity is changed by it. Finally, numerical simulations for automatic berthing are carried out, and the suggested control system is proved to be more practical under disturbance circumstances.

• International Journal of Aeronautical and Space Sciences
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• 제5권1호
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• pp.30-38
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• 2004

This paper deals with a problem of automatic landing guidance and control ofthe longitudinal airplane motion under the wind shear turbulence. Adaptive gainscheduled PID control law is proposed in this paper. Fuzzy logic is the main part ofthe adaptive PID controller as gain scheduler. To illustrate the successful applicationof the proposed control law to the automatic landing control problem, numericalsimulation is carried out based on the longitudinal nonlinear airplane model excited bythe wind shear turbulence. The simulation results show that the automatic landingmaneuver is successfully achieved with the satisfactory performance and the gainadaptation of the control law is made adequately within the limited gains.

• 한국항해항만학회지
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• 제48권2호
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• pp.116-124
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• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.