• 전기학회논문지
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• 제61권2호
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• pp.291-297
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• 2012

In this paper, potential field algorithm was used for path planning in dynamic environment. This algorithm is used to plan a robot path because of its elegant mathematical analysis and simplicity. However, there are some problems. The problems are problem of collision risk, problem of avoidance path, problem of time consumption. In order to solve these problems, we fused potential field with fuzzy system. The input of the fuzzy system is set using relative velocity and location of robot and obstacle. The output of the fuzzy system is set using the weighting factor of repulsive potential function. The potential field algorithm is improved by using fuzzy potential field algorithm and, path planning in various environment has been done.

• 한국항공운항학회지
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• 제26권2호
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• pp.47-53
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• 2018

In this paper, we investigate a collision avoidance algorithm for unmanned aerial vehicles using potential field based on the relative velocity of obstacles. The potential field consists of the attraction force and the repulsive force that are generated for the target and the obstacles. And the field can be classified into the attractive potential field generated by the target and the repulsive potential field generated by the obstacle, respectively. In this study, we construct an attractive potential field as a function of the distance between the UAV and the target position. On the other hand, a repulsive potential field is created by a function of distance and the relative velocity of the obstacle with respect to the UAV. The proposed potential field based collision avoidance algorithm is evaluate through simulations.

• 한국정밀공학회지
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• 제15권6호
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• pp.107-115
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• 1998

A path planning using potential field method is very useful for the real-time navigation of mobile robots. However, the method needs high modeling cost to calculate the potential field because of complex preprocessing, and mobile robots may get stuck into local minima. In this paper, An efficient path planning algorithm for multiple mobile robots, based on the potential field method, was proposed. In the algorithm. the concepts of subgoals and obstacle priority were introduced. The subgoals can be used to escape local minima, or to design and change the paths of mobile robots in the work space. In obstacle priority, all the objects (obstacles and mobile robots) in the work space have their own priorities, and the object having lower priority should avoid the objects having higher priority than it has. In this paper, first, potential based path planning method was introduced, next an efficient collision-avoidance algorithm for multiple mobile robots, moving in the obstacle environment, was proposed by using subgoals and obstacle priority. Finally, the developed algorithm was demonstrated graphically to show the usefulness of the algorithm.

• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• 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.

• 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.

• 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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.404-406
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• 2002

In this paper, the method of image feature extraction is proposed. This method employ the energy field analysis, outlier removal algorithm and ring projection. Using this algorithm, we achieve rotation-translation-scale invariant feature extraction. The force field are exploited to automatically locate the extrema of a small number of potential energy wells and associated potential channels. The image feature is acquired from relationship of local extrema using the ring projection method.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.248-249
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• 2013

This study presents a potential field method for path planning to goal with a mobile robot in unknown environment. The proposed algorithm allows mobile robot to navigate through static obstacles, and find the path in order to reach the target without collision. This algorithm provides the robot with the possibility to move from the initial position to the final position (target). Stage and Player simulator is used to perform the robot motion and implement the potential field algorithm in C/C++ for performance evaluation. Two-dimensional terrain model is used to simulate the ability of robot in motion planning without any collision.