• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1944-1947
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• 2005

In this paper, the control of a prosthetic arm using the flex sensor signal is described. The flex sensors are attached to the biceps and triceps brchii muscle. The signals are passed a differential amplifier and noise filter. And then the signals are converted to digital data by PCI 6036E ADC. From the data, position and velocity of arm joint are obtained. Also motion of the forearm - flexion and extension, the pronation and supination are abstracted from the data by proposed algorithm. A two D.O.F arm with RC servo-motor is designed for experiment. The arm length is 200 mm, weight is 4.5 N. The rotation angle of elbow joint is $120^{\circ}$. Also the rotation angle of the wrist is $180^{\circ}$. Through the experiment, we verified the possibility of the prosthetic arm control using the flex sensor signal. We will try to improve the control accuracy of the prosthetic arm continuously.

• 전기학회논문지
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• 제63권2호
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• pp.277-283
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• 2014

This paper proposes robot localization using Fuzzy-Extended Kalman Filter algorithm of the mobile robots equipped with least sensors. In order to improve the accuracy of the localization, we usually add the sensors or equipment. However, it increases the simulation time and expenses. This paper solves this problem using only the odometer and ultrasonic sensors to get the localization with the Fuzzy-Extended Kalman Filter algorithm method. By inputting the robot's angular velocity, sensor data variation, and residual errors into the fuzzy algorithm, we get the sensor weight factor to decide the sensor's importance. The performance of the designed method shows by the simulation and Pioneer 3-DX mobile robot test in the indoor environment.

• 한국산업융합학회 논문집
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• 제21권3호
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2005년도 추계학술발표대회 논문집
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• pp.27-30
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• 2005

This paper studied the PVDF(polyvinylidene fluoride) and Acoustic Emission sensors characteristics of the laminated composite panels under the low velocity impact. The various impact test by changing impact height is performed on the instrumented drop weight impact tester. The STFT(short time Fourier transform) and WT(wavelet transform) are used to decompose the each sensor signals. A ultrasonic C-scan and digital scope are used to define damaged area in each case. The test result indicated that the individual sensor signals involve the damage initiation and development.

• 제어로봇시스템학회논문지
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• 제11권3호
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• pp.200-206
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• 2005

In this paper, a redundancy management system for aircraft is studied, and FDI (Fault Detection and Isolation) algorithm of inertial sensor system is proposed. UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional FDI method cannot isolate multiple faults in a triple redundancy system. In this paper, hardware based FDI technique is proposed, which combines a parity equation approach with the wavelet based technique, which is a model-free FDI method. To verify the effectiveness of the proposed FDI method, numerical simulations are performed.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.912-917
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• 2006

A strain gauge weight measuring instrumentation system was designed with RF sensor network facilities. In the sensor module system data conversion and a series of signal processing were totally equipped. 16 strain gauges are incoming sensors and each output of the strain gauge was amplified and filtered for proper analog signal processing. Several measuring instrumentation OP amps and general purposed OP amps were used. 12 bits A/D converters converted analog signals to digital bits and a PIC microprocessor controlled the 16 channels of strain gauges. RF RS232 modules were used for wireless communication between the PIC microprocessor and an Ethernet host far a remote sensor monitoring system development.

• 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.

• 센서학회지
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• 제28권5호
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• pp.334-339
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• 2019

In this study, we propose a compensation method of raw LiDAR data with noise and noise filtering for signal processing of LiDAR sensors during the development phase. The raw LiDAR data include constant errors generated by delays in transmitting and receiving signals, which can be resolved by LiDAR signal compensation. The signal compensation consists of two stage. First one is LiDAR sensor calibration for a compensation of geometric distortion. Second is walk error compensation. LiDAR data also include fluctuation and outlier noise, the latter of which is removed by data filtering. In this study, we compensate for the fluctuation by using the Kalman filter method, and we remove the outlier noise by applying a Gaussian weight function.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3145-3162
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• 2023

As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.

• 한국정보과학회논문지:데이타베이스
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• 제37권6호
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• pp.324-332
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• 2010

실시간 임베디드 센서 네트워크 시스템에서의 이벤트 감지는 대부분 현실세계에서 수집된 센서 데이터들의 조합에 기반한다. 이에 최근에 이루어진 연구들에선 센서 데이터들을 수집, 집계하는 낮은 수준의 다양한 메커니즘들을 제안하였다. 그러나 실시간에서 연속적으로 발생하는 복잡한 이벤트들의 감지와 다양한 종류의 센서들로부터 입력되는 실시간 데이터의 처리를 위한 시스템에 대한 솔루션은 보다 많은 연구를 필요로 한다. 즉, 경량의 데이터 혼합이 가능하고 많은 컴퓨팅 자원을 필요로 하지 않는 실시간 이벤트 감지 기법이 필요하다. 이벤트 감지 프레임워크는 실시간 모니터링과 센서 데이터의 도착으로 일어나는 데이터 융합 메커니즘을 통하여 적시성과 임베디드 센서 네트워크의 자원 요구량을 감소시킬 수 있는 잠재력을 지니고 있다. 또한 임베디드 센서 네트워크 시스템이 신뢰성을 지닐 수 있도록 하기 위한 기반 기술인 프라이버시를 보장할 수 있는 익명화 기술을 설명한다.