• 한국통신학회논문지
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• 제39C권1호
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• pp.82-89
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• 2014

최근 M2M/IoT에 대한 관심이 높아지면서 디바이스의 위치와 자세 등을 인식할 수 있는 동작 인식 센서의 필요성이 대두되고 있다. 본 논문에서는 소형의 디바이스에 적합하도록 저잡음, 저전력, 초소형 6축 관성센서 IC를 구현하였다. 본 논문에서 구현된 IC는 3축의 압전형 자이로 센서와 3축의 압저항형 가속도 센서를 사용하며, 3축의 자이로스코프 감지 회로, 자이로스코프 센서 구동 회로, 3축의 가속도 감지 회로, 16bit sigma-delta ADC, 디지털 필터와 제어 회로로 구성되어 있다. 본 IC은 TSMC $0.18{\mu}m$ mixed signal CMOS공정으로 개발되었으며, STM사의 6축 관성 센서인 LSM330의 소비전류 6.1mA보다는 약 27% 낮은 4.5mA의 소비 전류로 동작한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 추계학술대회 논문집
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• pp.570-574
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• 1993

This paper proposes a new method of estimating the position and heading angle of a mobile robot moving on a flat surface. The proposed localization method utilizes two passive beacons and a single rotating ultrasonic sensor. The passive beacons consist of two cylinders with different diameters and reflect the ultrasonic pulses coming from the sonar sensor mounted on the mobile robot. The geometric parameter set of beacon is acquired from the sonar scan data obtained at a single mobile robot location using a new data processing algorithm. Form this parameter set, the position and heading angle of the mobile robot is determined directly. The performance and validity of the proposed method are evaluated using two beacons and a single sonar sensor attached at the pan-tilt device mounted on a mobile robot, named LCAR, in our laboratory.

• 한국태양에너지학회 논문집
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• 제29권1호
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• pp.38-43
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• 2009

In this paper. a prototype of a mobile Sun tracking system is proposed. The proposed system uses 2-axis tilt sensor and 3-axis magnetic sensor to measure the orientation and the posture of the system according to the horizontal system of coordinates, which are used to compensate the slope effects. Then through astronomical calculation using the time and position information obtained by GPS sensor the azimuth and altitude of the Sun from that location is calculated. The position of the Sun is converted to that of the mobile Sun tracking system coordinates and used to control A-axis and C-axis of the system.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.85-94
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• 2021

The LPR system's trigger sensor makes problem occasionally due to the heave weight of vehicle or the obsolescence equipment. If we replace the hardware sensor to the deep-learning based software sensor in order to generate the trigger signal, LPR system maintenance would be a lot easier. In this paper we proposed the deep-learning sliding window based object detection and tracking algorithm for the LPR system's trigger signal generation. The gate passing vehicle's license plate recognition results are combined into the normal tracking algorithm to catch the position of the vehicle on the trigger line. The experimental results show that the deep learning sliding window based trigger signal generating performance was 100% for the gate passing vehicles including the 5.5% trigger signal position errors due to the minimum bounding box location errors in the vehicle detection process.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1046-1048
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• 2003

Recently, various researches in respect of the positioning technologies using satellites and the other sensors have made location-based services (LBS) more common and accurate. Consequently, concern about position information has been increasing. However, since these positioning systems only focus on user's position, it is difficult to know the user's attitude or detailed behaviors at the specific position. It is worthy to study on how to acquire such human attitude or behavior, because those information is useful to know the context of the user. In this paper, the sensor unit consisting of three dimensional accelerometer was attached to human body, and autonomously measured the perpendicular acceleration of ordinary human behaviors including activity modes such as walking, running, and transportation mode using transportation such as a train, a bus, and an elevator. Subsequently, using the classified measurement results, the method to identify the human activity modes was proposed.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.215-221
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• 2010

This paper introduces development of location estimation and navigation system of mobile robots using USN and LEGO Mindstorms NXT. Developed system includes location estimation, location and navigation information display and navigation control parts. It used ZigBee based USN which was built with CC2431 chip to locate blind node and implemented fuzzy model to improve ability of calculation of distances from reference nodes and location of mobile robots. This paper proposed combination method of location estimation using USN and encoder which is built in motors of mobile robots. Experimental results showed proposed method is superior to the method which used USN only in location estimation and navigating robots. Developed system can locate current position of mobile robots and monitor information from sensor nodes like temperature, humidity and send control signal to mobile robot to move.

• 제어로봇시스템학회논문지
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• 제21권1호
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• 전기학회논문지
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• 제63권3호
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• pp.409-413
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• 2014

GIS partial discharge that occurred in the UHF band signal is effectively detected by the method to IEC60270 5pc the apparent minimum discharge can be detected over the GIS arrangement of the sensor interior and exterior of the UHF in accordance with the optimized position signal by considering the damping ratio is selected so that the signals can be obtained to be mounted. 362kV, 800kV GIS is installed on the internal and external sensors are UHF band signal attenuation is set by measuring the reference value, but the operation, 170kV case 362kV, 800kV on the basis of the measurement data and to be installed and operated. When 170kV per 1Bay by installing the built-in sensor 1 for detecting a partial discharge signal, But, GIS signal attenuation is large in the case of an internal partial discharge signal is not detected in some cases. Where the attenuation is great UHF signal of the sensor by increasing the quantity of partial discharge signals were acquired to allow relocation. The greater the spacing between the sensor and the sensor is applied simplifies the installation and reduces the cost in terms of maintenance of appropriate optimal position is calculated to detect the partial discharge signal is needed. Thus 170kV GIS signal power attenuation of a partial discharge by measuring the UHF sensor, and by relocating the proper position is calculated in accordance with the sensor signal decay rate and minimize the error of omission in detecting a partial discharge signal was optimized.

• 한국생산제조학회지
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• 제8권6호
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• pp.26-34
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• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• 한국컴퓨터정보학회논문지
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• 제28권1호
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• pp.49-54
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• 2023

GPS(Global Positioning System)는 군사 목적으로 개발되었고, 민간인 신호(GPS L1주파수 C/A 신호)를 개방하면서 많은 발전이 이루어졌다. 현재의 위성은 하루 약 2회 주기로 지구를 공전하며 위치를 측정하는데 위성 신호 3개(초기에는 시각 오차까지 계산하기 위하여 4개)이상을 수신하는데 전파 출발 시간에서부터 수신된 위성 신호의 전파 도달 시간(TOA)까지의 데이터를 삼변측량 방식을 통해 지상 수신기 3차원 위치를 결정한다. 그러나 GPS를 활용한 내비게이션의 경우 보통 5~10m의 위치 오차가 발생하며 아파트와 실내, 터널, 공장지대 및 산악 지대 등, 많은 지역이 GPS의 사각지대 또는 오차 범위 밖의 무력화 지역으로 존재하고 있다. 따라서 GPS 위성 신호의 수신이 불가능한 지역에서 현재의 위치 정보를 획득하기 위해서는 다른 방안이 제시되어야 한다. 본 연구에서는 가속도와 자이로 센서가 결합된 IMU(Inertial Measurement Unit)와 지자기 센서를 이용하여 GPS 신호 수신이 불가능한 지형에서도 위치인식이 가능하도록 시스템을 설계 하였다. 9-DOF IMU와 지자기 센서를 이용한 순간 속도 값을 계산하여 현재의 위치를 추적할 수 있는 방안을 연구 하였으며 제작과 실험을 통해 그 타당성을 검증하였다.