• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.42-47
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• 2010

Many contests by micro mouse was celebrated of which maze search algorithms performance are compared. That is used in various forms based on left(right) weight method, euclidean algorithm method, hill climbing method. However we feel uncomfortable to test algorithms performance through direct development of programs or hardwares as no software platform to test in maze search algorithms. In this research we develop of a platform for maze search algorithms that is easily to produce various forms of maze that are hard to be realized by hardware, to apply algorithms, and evaluate the seek time, operation count, steps and performance. The platform is consist of main layer, interface layer, user layer which has merit to apply and replace easily algorithms. We verified that the maze search algorithm can be applied even in the development and experiment of algorithm by evaluating and analyzing its performance through the experiment of platform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.188-191
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• 2011

Path finding and path planning is crucial in today's world where time is an extremely valuable element. It is easy to plan the optimum path to a destination if provided a map but the same cannot be said for an unknown and unexplored environment. It will surely be exhaustive to search and explore for paths to reach the destination, not to mention planning for the optimum path. This is very much similar to finding for an exit of a maze. A very popular competition designed to tackle the maze solving ability of autonomous called Micromouse will be used as a guideline for us to design our maze. There are numerous ways one can think of to solve a maze such as Dijkstra's algorithm, flood fill algorithm, modified flood fill algorithm, partition-central algorithm [1], and potential maze solving algorithm [2]. We will analyze these algorithms from various aspects such as maze solving ability, computational complexity, and also feasibility to be implemented.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.49-55
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• 2017

Robots, games and life applications have been developed while computer areas are developed. Moreover, various applications have been utilized for various users including the early childhood. Recently, smart phones have been dramatically used by various users including early childhood. Many applications need to find a path from a starting point to destinations. For example, without using real maps, users can find the direct paths for the destinations in realtime. Specifically, path exploration in game programs is so important to have accurate results. Nowadays, with these techniques, diverse applications for educations of early childhood have been developed. To deal with the functions, necessity of efficient path search programs with high accuracy becomes much higher. In this paper, we design and develop a friendly maze program for early childhood based on a path searching algorithm. Basically, the path of lineal distance from a starting location to destination is considered. Moreover, weight values are calculated by considering heuristic weighted h(x). In our approach, A* algorithm searches the path considering weight values. Moreover, we utilize depth first search approach instead of breadth first search in order to reduce the search space. so it is proper to use A* algorithm in finding efficient paths although it is not optimized paths.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.671-674
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• 2005

This paper describes the development of an optimal maze path game as web-based game contents. Client suer using web can access and run java applet program with download of java byte code with the independence of hardware system. The optimal maze path game developed in this paper consists of random maze path generation module, selected path input module, weighted optimal path search module, and path comparison module, selected path input module, weighted optimal path search module, and path comparison module. It enhances the cognition faculty of game users with the comparison of the maze path searched by optimal path search algorithm and the selected maze path by game users.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.333-338
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• 2005

This paper presents the target object search algorithm under Dynamic Programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation of Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved whether the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using our real robot.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.113-116
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• 2007

This paper describes the development of an optimal 3D maze path game as web-based game contents. Client user using web can access and run java applet program with download of java byte code with the independence of hardware system. The optimal 3D maze path game developed in this paper consists of random maze path generation module, selected path input module, weighted optimal path search module, and path comparison module. It enhances the cognition faculty of game users with the comparison of the maze path searched by optimal path search algorithm and the selected maze path by game users.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4167-4173
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• 2010

ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. It means that goal of computer education is improving problem-solving abilities not using of commercial software. So this paper suggests problem-solving method of maze escape through robots' cooperation in an effort of learning these elements. Problems robots should solve are first-search and role-exchange. First-search problem is that first robot searches maze and send informations about maze to the second robot in real time. Role-exchange problem is that first robot searches maze, but loses its function at any point. At this time second robot takes a role of first robot and performs first robot's missions to the end. To solve these two problems, it goes through four steps; problem analysis, algorithm description, flowchart and programming. Additional effects of our suggestion are chance of cooperation among students and use of queue in data structure. Further researches are use of more generalized mazes, application to real field and a talented curriculum.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.626-631
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• 2005

This paper presents the target object search algorithm under dynamic programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved if the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using a real robot.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.43-54
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• 1996

This paper presents new heuristic search algorithms for searching rectilinear r(L1), link metric, and combined shortest paths in the presence of orthogonal obstacles. The GMD(GuidedMinimum Detour) algorithm combines the best features of maze-running algorithms and line-search algorithms. The SGMD(Line-by-Line GuidedMinimum Detour)algorithm is a modiffication of the GMD algorithm that improves efficiency using line-by-line extensions. Our GMD and LGMD algorithms always find a rectilinear shortest path using the guided A search method without constructing a connection graph that contains a shortest path. The GMD and the LGMD algorithms can be implemented in O(m＋eloge＋NlogN) and O(eloge＋NlogN) time, respectively, and O(e＋N) space, where m is the total number of searched nodes, is the number of boundary sides of obstacles, and N is the total number of searched line segment. Based on the LGMD algorithm, we consider not only the problems of finding a link metric shortest path in terms of the number of bends, but also the combined L1 metric and Link Metric shortest path in terms of the length and the number of bands.