• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.134.6-134
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• 2001

The purpose of navigation algorithm is to reach a given target point without collision with obstacles while an autonomous mobile robot is navigating. To achieve a safe navigation, this paper presents an effective navigation algorithm for the autonomous mobile robot equipped with ultrasonic sensors in unknown environments. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The decision maker using fuzzy inference systems weights the steering angles selected ...

• 대한전기학회논문지:시스템및제어부문D
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• 제52권8호
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• pp.471-481
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• 2003

The acts of biological immune system are similar to the navigation for autonomous mobile robots under dynamically changing environments. In recent years, many researchers have studied navigation algorithms using artificial immune networks. Conventional artificial immune algorithms consist of an obstacle-avoidance behavior and a goal-reaching behavior. To select a proper action, the navigation algorithm should combine the obstacle-avoidance behavior with the goal-reaching behavior. In this paper, the neural network is employed to combine the behaviors. The neural network is trained with the surrounding information. the outputs of the neural network are proper combinational weights of the behaviors in real-time. Also, a velocity control algorithm is constructed with the artificial immune network. Through a simulation study and experimental results for a autonomous mobile robot, we have shown the validity of the proposed navigation algorithm.

• 초등상담연구
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• 제9권1호
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• pp.75-94
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• 2010

본 연구의 목적은 초등학교 4학년 학생들을 대상으로 수업행동의 개선을 위하여 수업행동을 수업 방해 행동과 수업 참여 행동으로 구분하고, 자기점검기법이 대상 아동들의 수업 방해 행동과 수업 참여행동에 어떠한 영향을 미치는지를 알아보고자 하는 데 있다. 이러한 연구목적을 달성하기 위해 설정한 연구문제는 첫째, 자기점검기법이 아동의 수업 방해 행동에 어떠한 영향을 미치는가. 둘째, 자기점검기법이 아동의 수업 참여 행동에 어떠한 영향을 미치는가를 밝히는 것이다. 연구 문제에 따른 연구 가설은 1. 자기점검기법은 아동의 수업방해행동을 감소시킬 것이다. 2. 자기점검 기법은 아동의 수업참여행동을 증가시킬 것이다로 세웠다. 연구 대상은 전라북도 J시에 소재하는 A초등학교 4학년 $\circledcirc$반 일반 학급 아동 12명으로 이는 기초선 기간의 행동측정 결과 수업 방해 행동 비율이 높은 8명과 수업 참여 행동 비율이 낮은 8명을 선정하였고, 양 쪽 그룹 모두에 속하는 아동이 4명이다. 이들의 사전 행동 관찰을 거쳐 개별적으로 수업 방해 행동 및 수업 참여 행동의 목표 행동을 설정하도록 하고, 기초선 1 기간 동안 각 행동의 빈도를 연구자가 두 명의 관찰자와 함께 측정하였다. 이후 중재 1 기간 동안 자기점검기법이 적용되었고, 아동 행동변화의 효과가 자기점검기법임을 밝히기 위하여 기초선 2 기간을 가졌다. 이후 중재 2 기간 동안 다시 자기점검기법이 실시되었으며, 10일 후 유지정도를 측정하기 위하여 사후 점검을 실시하였다. 개별 아동의 행동 발생 빈도를 변화 그래프를 이용하여 나타냈으며, 양적 결과의 제한점을 보완하기 위해 대상 아동들의 사후 소감문을 분석하였고, 연구자의 관찰내용을 제시하였다. 이 연구를 통해 얻어진 결과를 요약하면 첫째, 자기점검기법은 아동의 수업 방해 행동의 감소와 변화된 행동의 유지에 긍정적 효과를 미치는 것으로 나타났다. 둘째, 자기점검기법은 아동의 수업 참여 행동의 증가와 변화된 행동의 유지에 긍정적 효과를 미치는 것으로 나타났다.

• 한국자동차공학회논문집
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• 제20권3호
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• pp.67-76
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• 2012

In this paper, collision analysis of the full rake for the Next Generation High-speed EMU is conducted using a 3D/1D hybrid model, which combines 3-dimensional (3D) front-end structure of finite element model and 1-dimensional (1D) multi-body dynamics model in order to analyze train collision with a standard 3D deformable obstacle. The crush forces, passengers' accelerations and energy absorptions of a full rake train can be easily obtained through a simulation of a 1D dynamics model composed of nonlinear springs, dampers and masses. Also the obtained simulation results are very similar to those of a 3D model if an overriding behavior does not occur during collision. The standard obstacle in TSI regulation has been changed from a rigid body to a deformable body, and therefore 3D collision simulations should be conducted because their simulation results depends on the front-end structure of a train. According to the obstacle collision analysis of this study, the obstacle collides with the driver's upper structure after overriding over the front-end module. The 3D/1D hybrid model is effective to evaluate a main energy-absorbing module that is frequently changed during design process and reduce the need time of the modeling and analysis when compared to a 3D full car body.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.1055-1062
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• 1996

A method for automatically driving paddy vehicles, such as rice transplanters, etc., straight ahead in a paddy field was investigated . The direction of such vehicles must be precisely controlled to do the operations as straight. However, the alignment of the from wheels becomes distorted due to the unevenness of the ground, preventing the vehicle form going straight. If the proper alignment of the front wheels is maintained , the vehicle can be driven straight ahead greater precision. To investigate the influence of the ground uneveness, the behavior of a paddy vehicle running over an obstacle was quantified. The left wheel ran over an obstacle on a flat concrete road surfaced. When the steering wheel was free, the front wheels were forced toward the left when vehicle went up the obstacle and toward the right when the vehicle went down it. The torsion of the wheel when the vehicle went down the obstacle was larger than that when it went up ,so it turned right 5 degrees. Sinc hydraulic control steering decreased the steering angle , it turned right 3 degrees. These results suggest that a vehicle can be driven straight ahead with high precision when the steering angle is changed in response to the direction and inclination of the vehicle . Such results were obtained in a paddy field tests.

• 한국산업융합학회 논문집
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• 제17권2호
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1408-1412
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• 2004

This paper presents a method that a mobile robot finds location of doors in complex environments and safely traverses the door. A robot must be able to find the door in order that it achieves the behavior that is scheduled after traversing a door. PCA(Principal Component Analysis) algorithm using the vision sensor is used for a robot to find the location of door. Fuzzy controller using sonar data is used for a robot to avoid an obstacle and traverse the doors.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권3호
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• pp.245-249
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• 2012

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an 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 is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.159.2-159.2
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• 2005

• Advances in robotics research
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• 제1권1호
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• pp.101-126
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• 2014

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot's specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.