• 로봇학회논문지
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• 제6권3호
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• 한국공작기계학회논문집
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• 제11권6호
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• pp.60-67
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• 2002

A precise measurement of field test was performed to estimate the thermal performance of the forced convection electric air heater by experiment. Air temperature, flow rate and electrical power input were measured with the related measurement sensors, and acquisition methods for the measured data were studied to estimate the thermal performance of the tested air heater effectively. To determine the mean air temperature at the flow cross-section, measuring positions were chosen by considering the flow velocity profile and the equally divided cross-sectional area. From the experimental results, thermal efficiency was obtained accurately as an indication of the tested heating system performance.

• 센서학회지
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• 제14권1호
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• pp.52-55
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• 2005

Ni oxide thin films with thermal sensitivity superior to Pt and Ni thin films were formed through annealing treatment after Ni thin films were deposited by a r.f. magnetron sputtering method. Resistivity values of Ni oxide thin films were in the range of $10.5{\mu}{\Omega}cm$ to $2.84{\times}10^{4}{\mu}{\Omega}cm$ according to the degree of Ni oxidation. Also temperature coefficient of resistance(TCR) values of Ni oxide thin films depended on the degree of Ni oxidation from 2,188 ppm/$^{\circ}C$ to 5,630 ppm/$^{\circ}C$ in the temperature range of $0{\sim}150^{\circ}C$. Because of the high linear TCR and resistivity characteristics, Ni oxide thin films exhibit much higher sensitivity to flow and temperature changes than pure Ni thin films and Pt thin films.

• 한국군사과학기술학회지
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• 제14권5호
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• pp.768-773
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• 2011

The prediction method of future events using the time histories of velocity or pressure, etc., is a useful way for controlling various air vehicles. For example, the sensors of velocity or pressure can be used to extract the time mode coefficients of eigenmode of flow field, and then the result is applied to suppress wake or drag. The velocity information is mapped to the entire flow field, so this mapping function can be used to predict the future events based on the current information. The mapping function is composed of the huge amount of weight parameters, so the efficient way of finding these parameters is needed. Here, the neural network algorithm is studied to draw a mapping function using the number and location of velocity sensors.

• 로봇학회논문지
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• 제15권1호
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• pp.55-61
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• 2020

Getting on and off an elevator is one of the most important parts for multi-floor navigation of a mobile robot. In this study, we proposed the method for the pose recognition of elevator doors, safe path planning, and motion estimation of a robot using RGB-D sensors in order to safely get on and off the elevator. The accurate pose of the elevator doors is recognized using a particle filter algorithm. After the elevator door is open, the robot builds an occupancy grid map including the internal environments of the elevator to generate a safe path. The safe path prevents collision with obstacles in the elevator. While the robot gets on and off the elevator, the robot uses the optical flow algorithm of the floor image to detect the state that the robot cannot move due to an elevator door sill. The experimental results in various experiments show that the proposed method enables the robot to get on and off the elevator safely.

• 한국멀티미디어학회논문지
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• 제23권11호
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• pp.1372-1382
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• 2020

This paper proposes a core technology for a micro river monitoring terminal device suitable for flood monitoring in small rivers and valleys. Our proposed device is basically equipped with a 77GHz radar, gyro and accelerometer sensors. To measure the flow velocity and water level, we proposed a signal processing technique that extracts pure water energy components from the observed Doppler velocity and reflection intensity from the radar. And to determine the stability of the river structure equipped with our device, we constantly monitor the displacement of the measured values of the gyro and accelerometer sensors. Experimental result verified that our method detects pure water energy in various river environments and distinguishes between flow velocity and water level well. And we verified that vibration and position change of structures can be determined through a gyro sensor. In future research, we will work to build a secure digital twin river network by lowering the cost of supplying RF-WAV devices. Also we expect our device to contribute to securing a preventive golden time in rivers.

• 센서학회지
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• 제16권5호
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• pp.377-383
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• 2007

We describe the fabrication and characterization of a doubly clamped multi-walled carbon nanotube (MWNT). The device was assembled by an application of electric field in solution. The MWNT was clamped on end of metal trench electrodes in solution and deposited with additional platinum (Pt) on edge of electrode for firmly suspending the MWNT by focused ion beam (FIB). The MWNTs range of diameter and length were 100 to 150 nm and 1.5 to $2{\mu}m$, respectively. Electrical characteristics of fabricated devices were measured by I-V curve and impedance analysis. The mechanical deformation was observed by resistivity in high air pressure. Resonant frequency around 6.8 MHz was detected and resistivity was linearly varied according to the magnitude of air pressure. This device could have potential applications in nanoelectronics and various sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• 한국지능시스템학회논문지
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• 제6권4호
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• pp.92-101
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• 1996

차량의 증가와 도로 신장율의 저조로 교통체증은 날로 심해지고 있다. 이문제를 풀기 위한 한 방법은 교통류에 관한 실시간 정보를 얻어 교통신호를 동적으로 제어하는 것이다. 현재까지 교통류 정보를 얻기 위해 가장 많이 쓰인 것은 루프코일 인데 이것은 통과 차량의 평균속도를 측정하기 위해 필요한 차량 추적을 할 수 없는 단점이 있다. 따라서 이 문제를 해결하기 위해 영상 검지기가 출현하게 되었고 농담영상 혹은 칼라 영상열을 가정하고 있다. 본 논문에서는 칼라영상의 형태로 주어진 영상열에서 퍼지 클러스터리에 기반을 둔 이동 차량 추적 방법을 제안한다.

• 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.