• 전기전자학회논문지
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• 제24권1호
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• pp.232-237
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• 2020

본 논문에서는 자율주행 자동차에 물체를 인식하고 거리를 측정하는데 효율적인 센서 융합을 제안한다. 자율주행 자동차에 사용되는 대표적인 센서는 레이더, 라이다, 카메라이다. 이 중 라이다 센서는 차량 주변의 맵을 만드는 역할을 한다. 하지만 날씨 조건에 성능이 하락하고 센서의 가격이 매우 비싸다는 단점 있다. 본 논문에서는 이러한 단점을 보완하고자 비교적 저렴하고 눈, 비, 안개에 지장 없는 레이더 센서로 거리를 측정하며 차량 주변을 관찰한다. 물체 인식률이 뛰어난 카메라 센서를 융합하여 물체 인식 및 거리를 측정한다. 융합된 영상은 IP서버를 통해 실시간으로 스마트폰에 전송되어 현재 차량의 상황을 내부, 외부에서 판단하는 자율주행 보조 시스템에 사용될 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.417-421
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• 1992

Ultrasonic and vision data need to be fused for efficient object recognition, especially in mobile robot navigation. In the proposed approach, the whole ultrasonic echo signal is utilized and data fusion is performed based on each sensor's characteristic. It is shown to be effective through the experiment results.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2002년도 생물공학의 동향 (X)
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• pp.232-234
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• 2002

공업적으로 중요성이 날로 더해가는 phospholipase C (PLC) 를 Bacillus cereus를 이용하여 생산하였다. 또한, plc::gfp fusion protein 을 생산하는 재조합 E. coli 를 제조하고 배양하였으며 특히 형광센서를 이용하여 PLC 의 생산 특성을 모니터링하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.64.4-64
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• 2001

Localization is the key role in controlling the Mobile Robot. In this papers, a development of the sensor fusion algorithm for controling UTV(Unmanned Tracked Vehicle) is presented. The multi-sensocial dead-rocking subsystem is established based on the optimal filtering by first fusing heading angle reading from a magnetic compass, a rate-gyro and two encoders mouned on the robot wheels, thereby computing the deat-reckoned location. These data and the position data provoded by LBL system are fused together by means of an extended Kalman filter. This algorithm is proved by simulation studies.

• 제어로봇시스템학회논문지
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• 제18권8호
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2357-2360
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• 2002

For the satisfying performance of a oil lubricator, design of a oil controller for the system which meets the required specifications and its supporting hardware that keep their functioning is important. Among the hardware of a control system, oil system are most vulnerable to malfunction. Thus it is necessary to keep track of accurate and reliable oil readings for good fusion oil lubricator performance. In case of oil lubricator, data loss, ssr trigger error faults, they are detected by examining the data system output values and the major values of the system, and then the faults are recognized by the analysis of symptoms of faults. If necessary electronic-sensor values are synthesized according to the types of faults, and then they are used for the controller instead of the raw data. In this paper, a fast-32bit cpu microprocessor applied to the control of flexible link system with the sensor fault problems in the error modulo for exact positioning to show the applicability. It is shown that the fusion oil lubricator can provide a satisfactory loop performance even when the sensor faults occure.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.314-321
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• 2005

In this paper an intelligence embedding quadruped pet robot is described. It has 15 degrees of freedom and consists of various sensors such as CMOS image, voice recognition and sound localization, inclinometer, thermistor, real-time clock, tactile touch, PIR and IR to allows owners to interact with pet robot according to human's intention as well as the original features of pet animals. The architecture is flexible and adopts various embedded processors for handling sensors to provide modular structure. The pet robot is also used for additional purpose such like security, gaming visual tracking, and research platform. It is possible to generate various actions and behaviors and to download voice or music files to maintain a close relation of users. With cost-effective sensor, the pet robot is able to find its recharge station and recharge itself when its battery runs low. To facilitate programming of the robot, we support several development environments. Therefore, the developed system is a low-cost programmable entertainment robot platform.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.429-435
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• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.