• 한국컴퓨터정보학회논문지
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• 제14권11호
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• pp.31-40
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• 2009

가장 많이 활용하는 청소로봇의 청소기법은 크게 랜덤기법과 바둑판식기법으로 나눌 수 있다. 랜덤기법을 이용한 청소로봇은 장애물을 만날 때까지 직진 방향으로 청소를 수행하며, 장애물을 만나면 일정한 각도로 회전한 후 다시 직진 방향으로 청소를 수행한다. 랜덤기법은 중복적인 청소를 수행하는 문제가 빈번히 발생하며, 청소를 완료하는 데 오래 시간이 소요되는 단점이 있다. 바둑판식기법을 이용한 청소로봇은 장애물을 만날 때까지 직진 방향으로 청소를 수행하며, 장애물을 만나면 직진과 회전을 이용하여 청소가 수행되지 않은 위치로 이동하고, 이전에 청소를 수행한 방향의 반대로 청소를 수행한다. 바둑판식기법은 청소공간을 조밀하게 청소하며 진행하기 때문에 장애물이 없거나 작은 공간에서 작업 성능이 뛰어나다. 그러나 바둑판식기법으로 장애물이 있거나 복잡한 공간을 청소할 때는 청소시간이 증가한다. 그러므로 청소의 효율성을 증가시키기 위해서는 작업공간을 정확히 파악하여 청소를 계획적으로 진행해야 한다. 본 논문에서 제안한 가상지도 기반 청소로봇은 작업공간을 효율적으로 청소하는 특성을 갖는다. 시뮬레이션을 통해 제안한 기법의 효율성을 측정하였다.

• 스마트미디어저널
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• 제11권9호
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• pp.64-74
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• 2022

해양자원을 활용하기 위한 수중 로봇과 관련된 연구가 다수 진행되고 있다. 그러나 일반 드론과 다르게 수중 로봇은 매개체가 공기가 아닌 물이기 때문에 위치 파악이 쉽지 않은 문제점이 존재한다. 수중 위치를 확인하기 위한 기존 연구인 수중 로봇의 모니터링 및 포지셔닝 프로그램은 대규모 공간에서 활용하기 위한 목적을 가지고 있기 때문에 소규모의 공간에서 위치 파악 및 모니터링에 어려움을 가지고 있다. 이에 본 논문에서는 소규모 공간에서 지속적인 모니터링과 명령 전달을 위한 3차원 포지셔닝 프로그램을 제안한다. 제안된 프로그램은 수중 로봇의 위치에 깊이를 확인할 수 있도록 다차원 포지셔닝 모니터링 기능과 3차원 화면을 통해 이동 경로 제어할 수 있는 기능으로 구성된다. 성능평가를 통해 수중 로봇이 수조 모습과 동일하게 출력되어 3차원 화면으로 다양한 각도에서 모니터링 확인이 가능하였으며, 설정 경로와 실제 위치의 차이가 평균 6.44m 이내로써 상정 범위 내의 오차를 확인하였다.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2005년도 추계학술대회 논문집
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• pp.365-368
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• 2005

This paper describes the implementation of autonomy in the motion of a small size human robot. Traditional modeling of environment and concept of moving planning have limitations to adapt the change of environment and to implement in real-time operation. To overcome these limitations, we designed a behavior-based control algorithm and applied to robot soccer. Based on experiment, we verify that the behavior-based control algorithm works well in the change of environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.690-693
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• 2004

This paper proposes a multi-resolution electrostatic potential field (MREPF) based solution to the mobile robot path planning and collision avoidance problem in 2D dynamic environment. The MREPF is an environment method in calculation time and updating field map. The large scale resolution map is added to EPF and this resolution map interacts with the small scale resolution map to find an optimal solution in real time. This approach can be interpreted with Atlantis model. The simulation studies show the efficiency of the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제21권6호
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• pp.565-570
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• 2015

Supervised machine learning has become popular in discovering context descriptions from sensor data. However, collecting a large amount of labeled training data in order to guarantee good performance requires a great deal of expense and time. For this reason, semi-supervised learning has recently been developed due to its superior performance despite using only a small number of labeled data. In the existing semi-supervised learning algorithms, unlabeled data are used to build a graph Laplacian in order to represent an intrinsic data geometry. In this paper, we represent the unlabeled data as the spatial-temporal dataset by considering smoothly moving objects over time and space. The developed algorithm is evaluated for position estimation of a smartphone-based robot. In comparison with other state-of-art semi-supervised learning, our algorithm performs more accurate location estimates.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집D
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• pp.414-418
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• 2001

Flow and thermal characteristics of cooling system for the robot controller were numerically as well as experimentally investigated. To obtain the overall flows within controller, the system level solutions were analysed at first and then the board level solutions were pursued to understand the detailed flow and temperature fields near the main board which have a significant influence on the cooling of electronic components. The evaluation for a performance of the heat exchanger was conducted on the basis of the obtained flow and temperature patterns. The results showed that the heat exchanger made a small contribution to the cooling of controller and caused an increase of the temperature in CPU.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.817-822
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• 2004

This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• 한국정밀공학회지
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• 제31권8호
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• pp.697-703
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• 2014

This paper is study of solving vibration problem occurred in moving hand of wafer transfer robot in semiconductor manufacturing line. Long settling time for decreasing vibration makes low production rate, and moreover the excessive vibration of hand sometimes breaks the wafer in a cassette. The ways of reducing the moving speed and changing the type of motion profile did not help for lessening vibration. Therefore, we analyzed the mechanical property of the hand such as natural frequency, and frequency component of the motion profile currently used in the manufacturing line. In several conditions of motion profile, we found the best condition of which the frequency component in near of natural frequency of the hand is minimal and this induced small vibration in moving hand. The results were verified theoretically and experimentally using frequency analysis.

• 한국정밀공학회지
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• 제23권3호
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• pp.94-101
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• 2006

A global path planning method using self-organizing feature map which is a method among a number of neural network is presented. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector On the other hand, the modified method in this research uses a predetermined initial weight vectors of 1-dimensional string and 2-dimensional mesh, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are moved toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.

• 대한음성학회지:말소리
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• 제57호
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• pp.85-97
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• 2006

This paper suggests an algorithm that can estimate the direction of the sound source in real time. The algorithm uses the time difference and sound intensity information among the recorded sound source by four microphones. Also, to deal with noise of robot itself, the Kalman filter is implemented. The proposed method can take shorter execution time than that of an existing algorithm to fit the real-time service robot. Also, using the Kalman filter, signal ratio relative to background noise, SNR, is approximately improved to 8 dB. And the estimation result of azimuth shows relatively small error within the range of ${\pm}7$ degree.