• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.250-254
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• 2001

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.312-318
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• 2003

We propose a new technique for the cruise control system design of a mobile robot with three drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized teaming architecture. It is proposed a learning controller consisting of too neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.199-203
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• 2000

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.214-216
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• 2000

본 논문에서는 유전자 프로그래밍을 이용하여 온라인 적응 학습이 가능 진화 하드웨어의 진화 전략을 구성하였다. 유전자 프로그래밍은 특유의 트리형 개체구조가 여러 개의 프로세스의 합을 통한 복합 임무의 수행 구조로 해석될 수 있다는 이점에 비하여, 하드웨어 구현이 어렵고 crossover 연산자의 사용이 어렵다는 단점등에 의하여 진화 하드웨어의 동적 재구성 알고리즘으로 널리 사용되지 못하였다. 본 논문에서는 유전자 프로그래밍의 이러한 단점을 극복할 수 있는 개체 표현 및 하드웨어 구현 방법을 제안하였으며, 제안된 방법론에 기존의 연구 결과를 결합하여 유전자 프로그래밍의 수행 효율을 높일 수 있는 진화 전략을 구성하였다. 제안된 진화 전략은 자율 이동 로봇 실험에 적용되어 효율성을 확인하였다.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.495-500
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• 2002

Recently, a service robot industry outstands as an up and coming industry of the next generation. Specially, there are so many research in self-steering movement(SSM). In order to implement SSM, robot must effectively recognize all around, detect objects and make a surrounding map with sensors. So, many robots have a sonar and a infrared sensor, etc. But, in these sensors, We only know informations about between the robot and the object as well as resolution faculty is of inferior quality. In this paper, we will introduce new algorithm that recognizes objects around robot and makes a two dimension surrounding map with a omni-direction vision camera and two stereo vision cameras.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.183-187
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• 2002

This paper proposes a remote control system that combines computer network and an autonomous mobile robot. We control remotely an autonomous mobile robot with vision via the internet to guide it under unknown environments in the real time. The main feature of this system is that local operators need a World Wide Web browser and a computer connected to the internet communication network and so they can command the robot in a remote location through our Home Page. This system offers an image compression method using motion H.263 concept which reduces large time delay that occurs in network during image transmission.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.130-134
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• 2000

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.1
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• pp.10-17
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• 2015

We describe a research about remote control of mobile robot based on voice command in this paper. Through real-time remote control and wireless network capabilities of an unmanned remote-control experiments and Home Security / exercise with an unmanned robot, remote control and voice recognition and voice transmission are possible to transmit on a PC using a microphone to control a robot to pinpoint of the source. Speech recognition can be controlled robot by using a remote control. In this research, speech recognition speed and direction of self-driving robot were controlled by a wireless remote control in order to verify the performance of mobile robot with two drives.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.208-214
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• 2001

본 논문은 시변 입력 지연을 포함한 Takagi-Sugeno (TS) 퍼지 시스템으로 표현 가능한 비선형 시스템을 위한 체계적인 제어기의 설계 기법을 제안한다. 입력 지연은 화학 공정 시스템, 인터넷 기반 가상 실험실, 자율 이동 로봇의 원격 제어등, 실제의 산업 현장에서 매우 빈번히 발생하는 현상이며 제어 시스템의 성능을 감소시키며, 안정성을 저해하는 요소로 알려져 있다. 따라서 본 논문에서 다루고자 하는 문제는 매우 실제적인 문제이며 반드시 해결하여야 할 문제이다. 본 논문은 Lyapunov-Razumikhin 안정 이론에 기반하여 TS 퍼지 모델 기반 제어기의 설계 조건을 제시한다. 최종적인 제어기의 설계 조건은 선형 행렬 부등식의 형태로 주어진다. TS 퍼지모델 기반 제어기가 안정화시킬 수 있는 입력지연의 상한 값을 최대화하기 위하여 이중 최적화 기법을 도입한다. 제안된 제어기 설계 기법의 우수성과 타당성을 입증하기 위하여 모의 실험을 수행하였다. 컴퓨터 시뮬레이션 결과, 본 논문에서 제안한 타당성을 입증할 수 있다.