• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.299-303
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• 1993

There can be two methods in control systems: one is to use a linear controller, the other is to use a nonlinear controller. The PID controller and the fuzzy controller can be said to belong the linear and the nonlinear controller respectively. In this paper, a new hybrid controller which is consist of the linear PID controller of which the gain is tuned and the nonlinear self tuning fuzzy controller is proposed. In the PID controller, an algorithm which parameterizes the proportional, the intergral, and the derivative gain as a single parameter is used to improve the performance of the PID controller. In the self tuning fuzzy controller, an algorithm which changes the shape of the triangle membership function and changes the scaling factor which is multiplied to the error and the error change. The evaluation of the performance of the suggested algorithm is carried on by the simulation for the Rhino XH-2 robot manipulator with 5 links revolute joints.

• 대한기계학회논문집
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• 제15권5호
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• pp.1447-1454
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• 1991

본 로봇은 wheeled type과 legged type의 장점을 함께 가지고 있으므로 주행 속도가 빠르며 환경적응력이 좋다. 기존 로봇과 비교할때 Y.Icihkawa등이 개발한 HLV와 가장 유사하지만 모터 3개로 6개의 바퀴-다리 유닛을 구동하므로 모터15개로 5개의 바퀴-다리유닛을 구동하는 Ichikawa HLV와 동력전달구조에서 많이 상이하다. 뿐만아니라 본 로봇은 3개의 모터만 사용했기 때문에 주행제어가 훨씬 간단하고 제작 비가 저렴하며 장애물 및 계단승강시 걸음새가 훨씬 간단하다.(Ichikawa HLV 경우 뒷 쪽 2개의 다리를 동시에 들 수 없기 때문에 계단 승강시 몸체 회전을 적절하게 섞어야 한다.)

• 로봇학회논문지
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• 제5권2호
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• pp.127-134
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• 2010

In this paper, a hybrid semi-3D path planning algorithm combining Virtual Tangential Vector(VTV) and fuzzy control is proposed. 3D dynamic environmental factors are reflected to the 2D path planning model, VTV. As a result, the robot can control direction from 2D path planning algorithm VTV and speed as well depending on the fuzzy inputs such as the distance between the robot and obstacle, roughness and slope. Performances and feasibilities of the suggested method are demonstrated by using Matlab simulations. Simulation results show that fuzzy rules and obstacle avoidance methods are working properly toward virtual 3D environments. The proposed hybrid semi-3D path planning is expected to be well applicable to a real life environment, considering its simplicity and realistic nature of the dynamic factors included.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.36.5-36
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• 2001

Localization is one of the key problems in the navigation of autonomous mobile robots. The probabilistic Markov localization approaches offer a good mathematical framework to deal with the uncertainty of environment and sensor readings but their use for realtime applications is limited by their computational complexity. This paper aims to reduce the high computational cost associated with the probabilistic Markov localization algorithm. We propose a hybrid landmark-based localization method combining triangulation and probabilistic approaches, which can efficiently update position probability grid, while the probabilistic framework allows to make use of any available sensor data to refine robot´s belief about its current location. The simulation results show the effectiveness and robustness of the method.

• 로봇학회논문지
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• 제5권2호
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• pp.152-159
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• 2010

Finding a head of a person in a scene is very important for taking a well composed picture by a robot photographer because it depends on the position of the head. So in this paper, we propose a robust head tracking algorithm using a hybrid of an omega shape tracker and local binary pattern (LBP) AdaBoost face detector for the robot photographer to take a fine picture automatically. Face detection algorithms have good performance in terms of finding frontal faces, but it is not the same for rotated faces. In addition, when the face is occluded by a hat or hands, it has a hard time finding the face. In order to solve this problem, the omega shape tracker based on active shape model (ASM) is presented. The omega shape tracker is robust to occlusion and illuminationchange. However, whenthe environment is dynamic,such as when people move fast and when there is a complex background, its performance is unsatisfactory. Therefore, a method combining the face detection algorithm and the omega shape tracker by probabilistic method using histograms of oriented gradient (HOG) descriptor is proposed in this paper, in order to robustly find human head. A robot photographer was also implemented to abide by the 'rule of thirds' and to take photos when people smile.

• Journal of Welding and Joining
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• 제30권4호
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• pp.44-48
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• 2012

H-beam used for stiffening the upper structure of ocean plant is cut in the various shapes. The cutting process of the H-beam is done manually and requires a long time and high cost. Therefore, automation of H-beam cutting is an important task. This research aims to develop a 3-D simulator to build the automatic H-beam cutting system and to determine the optimal cutting method. The automatic H-beam cutting system composes of 6 robots including 2 cutting robots hang to a crane and 1 conveyer. The appropriate system layout for covering the various sizes and types of H-beam was tested and determined using the simulator. The H-beam cutting system uses a hybrid type of plasma and gas cutting because of special cutting shapes of H-beam. The cutting area of each cutting method should be properly divided according to the size and shape of H-beam to shorten the total cutting time. Additionally the collision between a robot and a robot or a robot and H-beam should be avoided. The optimal cutting method for the shortest cutting time without the collision could be found for the various cutting conditions by use of the simulator. 2 simulation samples shows the availability of the simulator to find the optimal cutting method.

• 한국정보통신학회논문지
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• 제25권6호
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• pp.785-791
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• 2021

본 연구는 서비스 로봇이 물건배달 서비스를 수행하기 위해 인식된 물체의 위치기반 정보로부터 최적의 작업 목적지를 추정하기 위한 방법론을 제안한다. 위치 추정 프로세스는 격자지도에 일반화된 보로노이 그래프를 적용하여 노드와 링크로 구성되는 초기 위상학 지도 작성, RGB-D센서를 이용하여 물체의 인식과 위치정보 추출, 장애물의 형상 및 거리정보를 수집한 후 ,무게중심법과 세선화를 병행하는 하이브리드 기법을 적용하여 서비스 로봇이 물건잡기 작업을 수행할 수 있는 최적의 이동위치를 추정하게 된다. 그런 다음, 노드 위치선정 규칙에 따라 추정된 위치와 기존 노드의 기하학적 거리비교를 통해 로봇의 작업 목적지에 대한 최적의 노드정보를 갱신하게 된다.

• 전자공학회논문지B
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• 제32B권12호
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• pp.1652-1662
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• 1995

In this paper, a hybrid neural network is proposed to improve the learning ability of a neural network. The union of the characteristics of a Self-Organizing Neural Network model and of multi-layer perceptron model using the backpropagation learning method gives us the advantage of reduction of the learning error and the learning time. In learning process, the proposed hybrid neural network reduces the number of nodes in hidden layers to reduce the calculation time. And this proposed neural network uses the fuzzy feedback values, when it updates the responding region of each node in the hidden layer. To show the effectiveness of this proposed hybrid neural network, the boolean function(XOR, 3Bit Parity) and the solution of inverse kinematics are used. Finally, this proposed hybrid neural network is applied to the visual tracking control of a PUMA560 robot, and the result data is presented.

• 한국정밀공학회지
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• 제30권9호
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• pp.909-913
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• 2013

Various types of large substrate handling robots are used in the thin file solar cell manufacturing line as well as LCD or PDP production line. Because the robot handles the heavy substrate at high speed, there are some issues such as vibration control and the optimal design of arms and forks. As the substrate becomes larger and heavier, robot systems are also larger and the vibration issue of the robot end-effector becomes more important. In the paper, we established the robot modeling and the control architecture including the flexible part such as forks. Then, we performed dynamic simulation in the various condition and analyzed the characteristics of the fork vibration. We can reduce the vibration using the trajectory planning and input shaping algorithm and it was proved by experiment.

• 제어로봇시스템학회논문지
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• 제14권2호
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.