• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.121-131
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• 2004

The K-shortest path algorithms are largely classified into two groups: oneis for finding loopless path (simple path), another loop paths. In terms of cimputational complexities, in general the loop-paths-finding ones are considered more efficient and easier to be handled than the loopless-paths-finding. The entire path deletion methods have been known as the best efficient algorithms among the proposed K-shortest path algorithms. These algorithms exploit the K-th network transformation to prevent the same path, which was already selected as the (K-1)th path, from being redetected. Nevertheless, these algorithms have a critical limitationto be applied in the practical traffic networks because the loops, in which the same modes and links can be unlimitedly repeated, are not preventable. This research develops a way to be able to selectively control loop-paths by applying link-label. This research takes an advantage of the link-based shortest path algorithms that since the algorithms can take care of two links simultaneouslyin the searching process, the generation of loops can be controlled in the concatenation process of the searched link and the preceded link. In concatenation of two links, since the precede link can be treated a sub-shortest to this link from the origination, whether both the node and the link of the searched link were already existed or not can be evaluated. Terefore, both the node-loopless path, in which the same node is not appeared, and the link-loopless, in which the same link is not appeared, can be separately controlled. Especially, the concept of the link-loopless path is expended to take into consideration reasonable route choice behaviors such as U-Turn, P-Turn, and Turn-Penalty, which are frequently witnessed in urban traffic network with intersections. The applicability of the proposed method is verified through case studies.

• Journal of KIISE
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• v.43 no.9
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• pp.1026-1033
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• 2016

Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.317-323
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• 2008

Mass transit information can contribute many benefits to users. Especially, transportation information technology is developing highly with information technology in Korea recently. Hereafter, it is expected to give customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithm in public transportation networks including travel and transfer attributes. In this research, constraints are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding condition arbitrarily is proposed by making the maximum value as variables. In this study, transfer frequency, total travel time, seat confirmation, transfer time and travel time become constraint condition based on k path finding algorithm considering service time constraint condition. Moreover, case study about user customized transfer information is performed in Seoul and metropolitan subway networks.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.71-77
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• 2004

While doing games, units have to find goal And according to algorism, there is great difference in time and distance. In this paper the researcher compared and described characteristics of each of the improved algorism and A* algorism by giving depth-first search, breadth-first search and distance value and then argued algorism. In addition. by actually calculating the presumed value in A* a1gorism, the researcher finds the most improved value. Finally, by means of comparison between A* algorism and other one, the researcher verified its excellence and did simple path-finding using A* algorism.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.447-449
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• 2004

We proposed the method of the production of the humanoid biped robot and apply the A* path finding algorithm, for that robot mainly used in game and mobile robot, to avoid obstacles at real time. Actually we made the robot which has 20 DOF, 12 DOF in the two legs, 6 DOF in the two arms and each 1 DOF in the neck and waist, to realize human motions with minimal DOF, And we use the CATIA V5 for 3D modeling design and simulate.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.527-529
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• 2006

In this paper, we find a robot's path using a Virtual Reality Modeling Language and overlay vision. For correct robot's path we describe a method for localizing a mobile robot in its working environment using a vision system and VRML. The robt identifies landmarks in the environment, using image processing and neural network pattern matching techniques, and then its performs self-positioning with a vision system based on a well-known localization algorithm. After the self-positioning procedure, the 2-D scene of the vision is overlaid with the VRML scene. This paper describes how to realize the self-positioning, and shows the overlap between the 2-D and VRML scenes. The method successfully defines a robot's path.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.83-92
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• 2018

This paper uses the Apollonius Circle technique to estimate the position of a target that generates a specific signal by using a drone, which is rapidly becoming a rapidly expanding industry. The existing direction finding method is performed through the vehicle on the ground or installed the antenna at a high position to detect the position of the target. However, the conventional direction finding method is difficult to configure the reception environment of the LOS signal, It is difficult. However, the direction finding using the drone is easy to construct and measure the LOS signal receiving environment using the drone flying at high altitude. In this study, we use the 3D 800MHz Path-Loss Model to reconstruct the signal by using the measurement data of the ground direction finding, reconstruct the signal by using the 3-D 800MHz Path-Loss Model, and use the Apollonius Circle method to estimate the position of the target. A simulation was performed to estimate the position of the target. Simulation was performed to determine the target position estimation performance by configuring the ground direction finding and the dron direction finding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.939-955
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• 2010

With the progress of IT and mobile positioning technologies, various types of location-based services (LBS) have been proposed and implemented. Finding a shortest path between two nodes is one of the most fundamental tasks in many LBS related applications. So far, there have been many research efforts on the shortest path finding problem. For instance, $A^*$ algorithm estimates neighboring nodes using a heuristic function and selects minimum cost node as the closest one to the destination. Pruning method, which is known to outperform the A* algorithm, improves its routing performance by avoiding unnecessary exploration in the search space. For pruning, shortest paths for all node pairs in a map need to be pre-computed, from which a shortest path container is generated for each edge. The container for an edge consists of all the destination nodes whose shortest path passes through the edge and possibly some unnecessary nodes. These containers are used during routing to prune unnecessary node visits. However, this method shows poor performance as the number of unnecessary nodes included in the container increases. In this paper, we focus on this problem and propose a new border line-based pruning scheme for path routing which can reduce the number of unnecessary node visits significantly. Through extensive experiments on randomly-generated, various complexity of maps, we empirically find out optimal number of border lines for clipping containers and compare its performance with other methods.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.418-418
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• 2000

This paper proposes a path planning algorithm for mobile robot. To generate an optimal path and minimum time path for a mobile robot, we use the Genetic Algorithm(GA) and Visibility Graph. After finding a minimum-distance between start and goal point, the path is revised to find the minimum time path by path-smoothing algorithm. Simulation results show that the proposed algorithms are more effective.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.663-668
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• 2010

In driving a car, turns such as left turns, right turns, or u-turns, make the speed of the car decrease considerably. A more straight path, therefore, is probably faster to arrive at the destination than zig-zag path with same distance. In this paper, we have newly proposed the turn heuristic to make more straight path. The path navigation algorithm with turn heuristic(called as TA* algorithm) could enhance the straightness of a path by putting the turned-edges to the turn cost. It requires higher cost to use TA* algorithm than traditional A* algorithm because the straight-edge first searching have increased the search space. We have improved the TA* algorithm into the variable TA* algorithm(called as VTA* algorithm) which adopt the turn-heuristic during the a portion of the whole path.