• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.430-433
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• 1996

In This paper, we design the developed path generation method which is named that CBPM(Continuous path generation method Based artificial Potential field) that is able to be used in the obstacles environment. This CBPM is designed so that it puts together two obstacle avoidance algorithm-the continuous path generation method and the artificial potential field method. Here, the continuous path generation method generate the safety path using continuous path curvature. But, this method has demerits when used in obstacles environment in which are closely located. Another method which is named the artificial potential field method generates the path with the artificial potential field in the obstacles environment. But, APFM has local minima in certain places and unnecessarily calculates the path in which obstacles are not located. So, the developed path generation method, CBPM, is suggested and performances in many different obstacles environments are shown by using computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1054-1059
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• 2005

The artificial potential method uses a potential field to guide a robot from a start to a goal configuration respectively. The potential field consists of attractive potential used to pull a robot toward a goal and repulsive potential to keep it away from obstacles. However, there are two problems concerning local minimum and computational cost to be resolved in conventional artificial potential methods. This study proposes a method utilizing a spline surface that interpolates arbitrary boundaries and a domain reduction method that reduces the unnecessary area. The proposed spline surface interpolates arbitrary shaped boundaries and is used as an artificial potential to guide a robot for global motion planning of a mobile robot. A reduced domain process reduces the unnecessary domain. We apply a distance-weighted function as such a function, which blends distances from each boundary with a reduction in computational time compared with other analytical methods. As a result, this paper shows that an arbitrary boundary spline surface provides global planning and a domain reduction method reduces local minimum with quick operation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.339-346
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• 2005

Artificial potential field (APF) is a widely used method for local path planning of autonomous mobile robot. So far, many different types of APF have been implemented. Once the artificial potential functions are selected, how to choose appropriate parameters of the functions is also an important work. In this paper, a detailed analysis is given on how to choose proper parameters of artificial functions to eliminate free path local minima and avoid collision between robots and obstacles. Two kinds of potential functions: Gaussian type and Quadratic type of potential functions are used to solve the above local minima problem respectively. To avoid local minima occurred in realistic situations such as 1) a case that the potential of the goal is affected excessively by potential of the obstacle, 2) a case that the potential of the obstacle is affected excessively by potential of the goal, the design guidelines for selecting appropriate parameters of potential functions are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.256-256
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• 2000

In this parer, we present a real-time path planning algorithm which is integrated the artificial potential field(APF) and simulated annealing(SA) methods for mobile robot. The APF method in path planning has gained popularity since 1990's. It doesn't need the modeling of the complex configuration space of robot, and is easy to apply the path planning with simple computation. However, there is a major problem with APF method. It is the formation of local minima that can trap the robot before reaching its goal. So, to provide local minima recovery, we apply the SA method. The effectiveness of the proposed algorithm is verified through simulation.

• Journal of Mechanical Science and Technology
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• 제17권12호
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• pp.1876-1885
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• 2003

The artificial potential field (APF) methods provide simple and efficient motion planners for practical purposes. However, these methods have a local minimum problem, which can trap an object before reaching its goal. The local minimum problem is sometimes inevitable when an object moves in unknown environments, because the object cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planing. In this study, we propose a new concept using a virtual obstacle to escape local minima that occur in local path planning. A virtual obstacle is located around local minima to repel an object from local minima. We also propose the discrete modeling method for the modeling of arbitrary shaped objects used in this approach. This modeling method is adaptable for real-time path planning because it is reliable and provides lower complexity.

• 정보과학회 논문지
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• 제42권10호
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• pp.1231-1238
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• 2015

본 논문은 신호등 신호에 따른 자율 주행 (또는 반-자율 주행) 차량의 주행 제어를 위한 인공 전위 함수(artificial potential function)를 제안한다. 신호등은 보행자의 안전과 직결된 일반적이면서도 가장 중요한 교통 신호 중 하나로서, 도로 위 자율 주행을 위해서는 차량이 교통 신호를 준수하게 해주는 주행 알고리즘의 설계가 중요하다. 본 논문은 세 가지 신호 색(녹색, 노랑, 빨강)으로 구성된 차량 신호등의 신호에 따라 차량의 움직임을 제어할 수 있는 인공 전위 함수를 제안한다. 제안된 인공 전위 함수는 세 가지 신호 색 각각에 대한 인공 전위 함수들로 구성되며, 신호에 따라 전위 함수가 전환되며 인공 전위 장(artificial potential field)을 변화시킨다. 제안된 신호등 전위 함수는 차량 주행을 위한 기존의 인공 전위 함수들과 결합되어 최종 인공 전위 장을 생성한다. 제안하는 방법은 시뮬레이션을 통해 다양한 신호등 상황에 대해 실험되었으며, 신호등의 신호에 따라 차량이 자연스럽게 반응하는 모습을 보여준다.

• 한국군사과학기술학회지
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• 제4권2호
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• pp.17-29
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• 2001

In this paper, we designed the hybrid path generation method which is named CAPM(Continuous path generation method based on artificial Potential field) that is able to be used in the obstacles environment. This CAPM was designed so that it puts together two obstacle avoidance algorithm-the continuous path generation method(CPGM) and the artificial potential field method(APFM). Here, the CAPM generate the safety path using continuous path curvature. But, this method has demerits when used in obstacles environment in which are closely located. Another method which is named the APFM generates the path with the artificial potential field in the obstacles environment. But, It has local minima in certain places and unnecessarily calculates the path in which obstacles are not located. So, the CAPM was designed for autonomous underwater vehicle(AUV) obstacle avoidance. As the result of simulation, it was confirmed that the CAPM can be applied to a safe path generation for AUV.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.710-712
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• 2006

The aim of this study was to analyze limestone deposits potential using an artificial neural network and a Geographic Information System (GIS) environment to identify areas that have not been subjected to the same degree of exploration. For this, a variety of spatial geological data were compiled, evaluated and integrated to produce a map of potential deposits in the Gangreung area, Korea. A spatial database considering deposit, topographic, geologic, geophysical and geochemical data was constructed for the study area using a GIS. The factors relating to 44 limestone deposits were the geological data, geochemical data and geophysical data. These factors were used with an artificial neural network to analyze mineral potential. Each factor’s weight was determined by the back-propagation training method. Training area was applied to analyze and verify the effect of training. Then the mineral deposit potential indices were calculated using the trained back-propagation weights, and potential map was constructed from GIS data. The mineral potential map was then verified by comparison with the known mineral deposit areas. The verification result gave accuracy of 87.31% for training area.

• 한국지능시스템학회논문지
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• 제22권4호
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• pp.476-480
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• 2012

본 논문에서는 선도 로봇을 추종하는 군집 로봇의 대형 제어를 인공 포텐셜 장을 사용하여 제안한다. 또한, 인공 포텐셜 장은 물리적으로 해석하기 쉬운 전기장을 모델링하여 구성하고, 장애물을 더욱 효과적으로 모델링하기 위해서, 장애물의 모양에 따라 전기장의식을 달리한다. 제안하는 방법은 선도 로봇의 경로를 인공 포텐셜 장을 통해 계획한 뒤, 선도 로봇을 추종 로봇이 뒤따라가는 형태로 구성된다. 마지막으로 시뮬레이션 예제를 통해 제안하는 기법의 타당성을 검증한다.

• 한국재료학회지
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• 제23권2호
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• pp.149-153
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• 2013

Delamination crack detection is very important for improving the structural reliability of laminated composite structures. This requires real-time delamination detection technologies. For composite laminates that are reinforced with carbon fiber, an electrical potential method uses carbon fiber for reinforcements and sensors at the same time. The use of carbon fiber for sensors does not need to consider the strength reduction of smart structures induced by imbedding sensors into the structures. With carbon fiber reinforced (CF/) epoxy matrix composites, it had been proved that the delamination crack was detected experimentally. In the present study, therefore, similar experiments were conducted to prove the applicability of the method for delamination crack detection of CF/polyetherethereketone matrix composite laminates. Mode I and mode II delamination tests with artificial cracks were conducted, and three point bending tests without artificial cracks were conducted. This study experimentally proves the applicability of the method for detection of delamination cracks. CF/polyetherethereketone material has strong electric resistance anisotropy. For CF/polyetherethereketone matrix composites, a carbon fiber network is constructed, and the network is broken by propagation of delamination cracks. This causes a change in the electric resistance of CF/polyetherethereketone matrix composites. Using three point bending specimens, delamination cracks generated without artificial initial cracks is proved to be detectable using the electric potential method: This method successfully detected delamination cracks.