• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.362-367
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• 2011

The collision-free path of a manipulator should be regenerated in the real time to achieve collision safety when obstacles or humans come into the workspace of the manipulator. A probabilistic roadmap (PRM) method, one of the popular path planning schemes for a manipulator, can find a collision-free path by connecting the start and goal poses through the roadmap constructed by drawing random nodes in the free configuration space. The path planning method based on the configuration space shows robust performance for static environments which can be converted into the off-line processing. However, since this method spends considerable time on converting dynamic obstacles into the configuration space, it is not appropriate for real-time generation of a collision-free path. On the other hand, the method based on the workspace can provide fast response even for dynamic environments because it does not need the conversion into the configuration space. In this paper, we propose an efficient real-time path planning by combining the PRM and the potential field methods to cope with static and dynamic environments. The PRM can generate a collision-free path and the potential field method can determine the configuration of the manipulator. A series of experiments show that the proposed path planning method can provide robust performance for various obstacles.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.163-173
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• 2010

In multi-mobile robot environment, path planning and collision avoidance are important issue to perform a given task collaboratively and cooperatively. The proposed approach is based on a potential field method and fuzzy logic system. For a global path planner, potential field method is employed to select proper path of a corresponding robot and fuzzy logic system is utilized to avoid collisions with static or dynamic obstacles around the robot. This process is continued until the corresponding target of each robot is reached. To test this method, several simulation-based experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.170-184
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• 2024

With the advancement of autonomous navigation technology in maritime domain, there is an active research on swarming Unmanned Surface Vehicles (USVs) that can fulfill missions with low cost and high efficiency. In this study, we propose a formation control algorithm that maintains a certain shape when multiple unmanned surface vehicles operate in a swarm. In the case of swarming, individual USVs need to be able to accurately follow the target state and avoid collisions with obstacles or other vessels in the swarm. In order to generate guidance commands for swarm formation control, the potential field method has been a major focus of swarm control research, but the method using the potential field only uses the position information of obstacles or other ships, so it cannot effectively respond to moving targets and obstacles. In situations such as the formation change of a swarm of ships, the formation control is performed in a dense environment, so the position and velocity information of the target and nearby obstacles must be considered to effectively change the formation. In order to overcome these limitations, this paper applies a method that considers relative velocity to the potential field-based guidance law to improve target following and collision avoidance performance. Considering the relative velocity of the moving target, the potential field for nearby obstacles is newly defined by utilizing the concept of Velocity Obstacle (VO), and the effectiveness and efficiency of the proposed method is verified through swarm control simulation, and swarm control experiments using a small scaled unmanned surface vehicle platform.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• Journal of the Korea Institute of Military Science and Technology
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• v.4 no.2
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.476-480
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• 2012

In this paper, artificial potential field(APF) is applied to formation control for the leader-following swarm robot. Furthermore, APF is constructed by applying the electrical field model. Moreover, to model the obstacle effectively, each obstacle has different form due to the electrical field equation. The proposed method is formed as two sub-objective: path planning for the leader-robot and following-robots following the leader-robot. Finally, simulation example is given to prove the validity of proposed method.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.