• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제25권4호
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• pp.149-161
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• 2021

This study proposes a methodology for mission/path planning of an unmanned aerial vehicle (UAV) using an artificial potential field with the Markov Decision Process (MDP). The planning problem is formulated as an MDP. A low-resolution solution of the MDP is obtained and used to define an artificial potential field, which provides a continuous UAV mission plan. A numerical case study is conducted to demonstrate the validity of the proposed technique.

• 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.

• 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.

• 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.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2000년도 춘계학술대회논문집
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• pp.71-74
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• 2000

The equi-potential lines designed in the electric field are introduced to find the preform shape in axisymmetric hot forging. The equi-potential lines generated between two conductors of different voltages show similar trends of the minimum work paths between the undeformed shape and the deformed shape. Base on this similarity the equi-potential lines obtained by arrangement of the initial and final shapes are utilized for the design of preform and then the artificial neural network is used to find the range of initial volume and potential value of the electric field.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2360-2362
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• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• 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.

• 전기학회논문지
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• 제64권10호
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• pp.1479-1485
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• 2015

Robot's technology was very simple and repetitive in the past. Nowadays, robots are required to perform intelligent operation. So, path planning has been studied extensively to create a path from start position to the goal position. In this paper, potential field algorithm was used for path planning in dynamic environments. It is used for a path plan of mobile robot because it is elegant mathematical analysis and simplicity. However, there are some problems. The problems are collision risk, avoidance path, time attrition. In order to resolve path problems, we amalgamated potential field algorithm with the artificial neural network system. The input of the neural network system is set using relative velocity and location between the robot and the obstacle. The output of the neural network system is used for the weighting factor of the repulsive potential function. The potential field algorithm problem of mobile robot's path planning can be improved by using artificial neural network system. The suggested algorithm was verified by simulations in various dynamic environments.

• 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.

• 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.