• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.25-32
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• 2015

The Genetic algorithm is a search algorithm using evaluation, genetic operator, natural selection to populational solution iteratively. The convergence and divergence characteristic of genetic algorithm are affected by selection strategy, generation replacement method, genetic operator when genetic algorithm is designed. This paper proposes fast convergence genetic algorithm for time-limited robot path planning. In urgent situation, genetic algorithm for robot path planning does not have enough time for computation, resulting in quality degradation of found path. Proposed genetic algorithm uses fast converging selection strategy and generation replacement method. Proposed genetic algorithm also uses not only traditional crossover and mutation operator but additional genetic operator for shortening the distance of found path. In this way, proposed genetic algorithm find reasonable path in time-limited situation.

• 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 IKEEE
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• v.25 no.3
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• pp.437-444
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• 2021

In this paper, we propose an autonomous driving algorithm that allows a robot to explore various terrains, and implement an application that can monitor the robot's movement path during terrain search. The implemented application consists of a status unit that indicates the position, direction, speed, and motion of the mobile robot, a map unit that displays terrain information obtained through terrain search, and a control unit that controls the movement of the mobile robot. In order to control the movement of the robot, only the start and stop of the search/return is commanded by the application, and all driving for the search is performed autonomously. The basic algorithm for terrain search uses an infrared sensor to check for obstacles in the order of left, front, right, and rear, and if there is no obstacle and the path traveled is a dead end, it returns to the previous position and moves in the other direction to continue the search. Repeat the process to explore the terrain.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.1-10
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• 2000

The traveling salesman problem is a representative NP-Complete problem. It needs lots of time to get a solution as the number of city increase. So, we need an efficient heuristic algorithm that gets good solution in a short time. Almost edges that participate in optimal path have somewhat low value cost. This paper discusses the property of nearest neighbor and 3-opt. This paper uses nearest neighbor's property to select candidate edge. Candidate edge is a set of edge that has high probability to improve cycle path. We insert edge that is one of candidate edge into intial cycle path. As two cities are connected. It does not satisfy hamiltonian cycle's rule that every city must be visited and departed only one time. This paper uses 3-opt's method to sustain hamiltonian cycle while inserting edge into cycle path. This paper presents a highly efficient heuristic algorithm verified by numerous experiments.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.233-242
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• 2009

This paper briefly reviews the path planning methods that are applicable to the autonomous mobile robots for the military. Two distinct path search algorithms, $A^*$ and $D^*$ that are most popular and flexible in public applications, among those reviewed are coded and analyzed in terms of combat environment assessment factors called METT+TC for the area of operations. The results imply that it is important to consider the characteristics of defense acquisition process and the specific requirements of defense operation so that the successful technology development of the Robot products is directly linked to the defense procurement of Robot products.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.368-376
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• 2007

How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.27-35
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• 1998

Navigation is a method to direct a mobile robot without collision when traversing the environment. This is to reach a destination without getting lost. In this paper, global and local path planning in fixed obstacle and moving obstacle using genetic algorithm are presented. First, mobile robot searches optimal global path using genetic algorithm without falling into local minima. Then if it finds a unknown obstacle, it searches new path without crashing obstacle. Also if there is a moving obstacle, mobile robot searches new optimal path without colliding with the obstacles. Various simulation results show the proposed algorithm can search a shortest path effectively.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.85-96
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• 2001

This paper discusses the problem of finding the Origin-Destination(O-D) shortest path in urban road networks that have variable special qualifies such as time windows for passing as well as geometrical special qualities such as U-turn and left-turn prohibition. The focus of this paper is motivated by the problem of finding minimum travel time paths for an advanced traveler information system (ATIS) in the context of intelligent transportation system(ITS) application. The transportation network with variable and geometrical special qualities is a more realistic representation of the urban road network in the real word. But, the traditional and existing shortest path algorithms can not search practical shortest path that variable special quality is reflected. This paper presents a shortest path algorithm which can search reasonable shortest path information for the urban ATIS application within a real time. The algorithm is based on genetic algorithm(GA). The high performance of the proposed algorithm is demonstrated by computer simulations.