• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1193-1196
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1603-1618
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• 2024

Emergency operation plans are indispensable elements for effective process safety management especially when unanticipated events occur under extreme situations. In the paper, a synthesis framework is proposed for the integration success path planning and performance analysis. Within the synthesis framework, success path planning is implemented through flow-directed signal tracing, renaming and reconstruction from a complete collection of Minimal Path Sets (MPSs) that are obtained using graph traversal search on GO-FLOW model diagram. The performance of success paths is then evaluated and prioritized according to the task complexity and probability calculation of MPSs for optimum action plans identification. Finally, an Auxiliary Feed Water System of Pressurized Water Reactor (PWR-AFWS) is taken as an example system to demonstrate the flow-directed MPSs search method for success path planning and performance analysis. It is concluded that the synthesis framework is capable of providing procedural guidance for emergency response and safety management with optimal success path planning under extreme situations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.206-209
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• 2005

Optimal path search systems to take continuously changed traffic flows into consideration is necessary in order to reduce the cost to get destination. However, to search optimal path in client terminals with low computing power yields high computational cost. Thus, a method with low cost and near optimal path as well is required. In this paper, we propose a path search method using variable heuristic for the sake of reducing operation time. The heuristic is determined by the change of the average speeds of cars located in grid which means a rectangle region.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.646-655
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• 2009

This paper presents a new search strategy based on models of evolution in order to solve the problem of collision-free robotic path planning. We designed the robot path planning method with genetic algorithm which has become a well-known technique for optimization, intelligent search. Considering the path points as genes in a chromosome will provide a number of possible solutions on a given map. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. The effectiveness of the proposed genetic algorithm in the path planning was demonstrated by simulation. The proposed search strategy is able to use multiple and static obstacles.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3160-3172
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• 1996

A search algorithm for the collision free, time optimal transport path of overhead cranes has been proposed in this paper. The map for the working environment of overhead cranes was constructed in the form of three dimensional grid. The obstacle occupied region and unoccupied region of the map has been represented using the octree model. The best-first search method with a suitable estimation function was applied to select the knot points on the collision free transport path to the octree model. The optimization technique, minimizing the travel time required for transporting objects to the goal while subjected to the dynamic constraints of the crane system, was developed to find the smooth time optimal path in the form of cubic spline functions which interpolate the selected knot points. Several simulation results showed that the selected estimation function worked effectively insearching the knot points on the collision free transport path and that the resulting transport path was time optimal path while satisfying the dynamic constraints of the crane system.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.824-830
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• 2010

It is not easy job to find a underwater target using sonar system in the ASW operations. Many researchers have tried to solve anti-submarine search problem aiming to maximize the probability of detection under limited searching conditions. The classical 'Search Theory' deals with search allocation problem and search path problem. In both problems, the main issue is to prioritize the searching cells in a searching area. The number of possible searching path that is combination of the consecutive searching cells increases rapidly by exponential function in the case that the number of searching cells or searchers increases. The more searching path we consider, the longer time we calculate. In this study, an effective algorithm that can maximize the probability of detection in shorter computation time is presented. We show the presented algorithm is quicker method than previous algorithms to solve search problem through the comparison of the CPU computation time.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.907-914
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• 2014

A heuristic search algorithm is proposed to plan a collision free path for robots in an indoor environment. The proposed algorithm is to find a collision free path in the gridded configuration space by proposed heuristic graph search algorithm. The proposed algorithm largely consists of two parts : tunnel searching and path searching in the tunnel. The tunnel searching algorithm finds a thicker path from start grid to goal grid in grid configuration space. The tunnel is constructed with large grid defined as a connected several minimum size grids in grid-based configuration space. The path searching algorithm then searches a path in the tunnel with minimum grids. The computational time of the proposed algorithm is less than the other graph search algorithm and we analysis the time complexity. To show the validity of the proposed algorithm, some numerical examples are illustrated for robot.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1333-1341
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• 2009

Tactical path-finding in computer games is path-finding where a path is selected by considering not only basic elements such as the shortest distance or the minimum time spend but also tactical information of surroundings when deciding character's moving trajectory. One way to include tactical information in path-finding is to represent a heuristic function as a sum of tactical quality multiplied by a weighting factor which is.. determined based on the degree of its importance. The choice of weighting factors for tactics is very important because it controls search performance and the characteristic of paths found. In this paper. we propose a method for improving a heuristic function by adjusting weights based on the difference between paths on examples given by a level designer and paths found during the search process based on the CUITent weighting factors. The proposed method includes the search algorithm modified to detect search errors and learn heuristics and the perceptron-like weight updating formular. Through simulations it is demonstrated how different paths found by tactical path-finding are from those by traditional path-finding. We analyze the factors that affect the performance of learning and show the example applied to the real game environments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.624-632
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• 2022

Relationship networks such as an interpersonal relationship network or navigation route search can be expressed in graph form. However, as the amount of data increase, there is a problem that it is difficult to search for the desired data when it is displayed on one screen. In this paper, we propose a visualization method for searching for people, searching for the shortest path between people, and using graphs to express an interpersonal relationship network with many nodes. Unlike the search for the shortest path in the routing table, the shortest path in the interpersonal relationship network should be changeable according to the intension or importance of the researcher or user who is analyzing it. To this end, the BFS algorithm was modified to apply the characteristics of the interpersonal relationship network. For the verification of the results, the data in the character relationship information of the Korean Classics DB in the Korean Classics Translation Institute was used.