• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.592-598
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• 2008

This paper presents collision prediction and avoidance method for AGVS (Automatic Guide Vehicle System). Also, we propose the PO(Right of Path Occupying) with decentralized delay time for collision avoidance. Classified essential element of AGV's working environment is modeled in this paper. Using this model, we propose a new shortest path algorithm using A* search algorithm and obtain the information on AGVs travel time, coordinates and rotation vector. Finally, we use the AGVs information data as input for simulation program. The simulation practice is used in order to evaluate a collision prediction and avoidance, and it has been presented to demonstrate the applicability of the minimize delay time.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.204-213
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• 1999

This paper suggests a numerical method of finding optimal geometric path and minimum-time motion for a manipulator arm. To find the minimum-time motion, the optimal geometric path is searched first, and the minimum-time motion is searched on this optimal path. In the algorithm finding optimal geometric path, the objective function is minimizing the combination of joint velocities, joint-jerks, and actuator forces as well as avoiding several static obstacles, where global search is performed by adjusting the seed points of the obstacle models. In the minimum-time algorithm, the traveling time is expressed by the linear combinations of finite-term quintic B-splines and the coefficients of the splines are obtained by nonlinear programming to minimize the total traveling time subject to the constraints of the velocity-dependent actuator forces. These two search algorithms are basically similar and their convergences are quite stable.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.2
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• pp.173-183
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• 1996

In this paper, a new structure that can do fault detection and location of digial logic circuits more efficiently using current testing techniques is proposed. In the conventional method, observation point for steady state power supply current was only one, but in the proposed method more fault classes are divided for fault detection and location through the ovservation of steady state power supply current at two points. Also, it is shown that this structure can be easily applied in detection of stuck-open fault which is not easy to do testing with conventional current testing techniques. In the presented mehtod, an extra trasnistor is used, and current path is made compulsorily in the CMOS circuits in which no current path can be established in steady state, then it can be known that stuck-open tault is in the MOS transistor on the considering current path, if this path disappears due to stuck-open fault. The validity and the effectiveness is shwon, thorugh the SPICE simulation of circuits with fault and the current path search experiment using current path search program based on transistor short model wirtten in C language on SUN sparc workstation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.565-569
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• 2007

To find optimal path is killer application in the telematics system. The shortest path of conventional system, however, isn't always optimal path. That is, the path with minimum travelling time could be defined as optimal path in the road networks. There are techniques and algorithms for finding optimal path. Hierarchical path algorithm categorizes road networks into major layer and minor layer so that the performance of operational time increases. The path searched is accurate as much as optimal path. At above 2 system, a method to allocate minor roads to major road region influences the performance extremely. This paper proposes methods to determine search space for selecting major roads in the hierarchical path algorithm. In addition, methods which apply the proposed methods to hierarchical route algorithm is presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1216-1223
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• 2018

As field of application of AMI, AMR uses the power line as the primary means of communication. PLC has a big merit without installation of the new network for communication in a field using the power line which is the existing equipment. However, there is a serious obstacle in commercialization for the instability by noise and communication environment. Therefore, the technical method for maintaining the communication state which overcome such demerit and was stabilized is required essentially. PLC routing technology is applied with the alternative plan now. The routing technology currently managed by field includes many problems by applying the algorithm of an elementary level. PLC routing path search problem can be modeled with the problem of searching for optimal solution as similar to such as optimal routing problem and TSP(Travelling salesman problem). In this paper, in order to search for a PLC routing path efficiently and to choose the optimal path, GA(Genetic Algorithm) was applied. Although PLC was similar in optimal solution search as compared with typical GA, it also has a difference point by the characteristic of communication, and presented the new methodology over this. Moreover, the validity of application technology was verified by showing the experimental result to which GA is applied and analyzing as compared with the existing algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.117-123
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• 2023

There are casualties due to inundation and flooding due to intensive typhoons or heavy rains in summer. Due to such damage, the biggest disaster is flood, and in order to reduce human damage, this paper proposes a shortest distance algorithm-based pedestrian path search study using Map API. This system selects Map API through comparative analysis and provides the shortest route. The route explored is in JSON format and the data of the shelter is stored in the database. The route search system designed and implemented based on this data locates pedestrians and provides evacuation routes in case of flash floods. In addition, if the route cannot be entered while moving to the evacuation route, the current location of the pedestrian is identified, the route is re-searched, and a new route is provided. Therefore, it is believed that the pedestrian route search system proposed in this paper will prevent negligent accidents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.219-221
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• 2022

In recent summer, as it is concentrated, even in mountainous areas, flooding and flooding cause casualties in pedestrian evacuation situations. To compensate for this, a system that detects the occurrence of flooding and allows pedestrians to evacuate safely is required. Therefore, in this paper, we propose a research on pedestrian path search based on the shortest distance algorithm using Map API. The pedestrian route search system outputs a map using the T Map API, selects nearby buildings as shelters, and stores data. A shelter close to the pedestrian's current location is selected, and the shortest route is output and the distance and time are provided. If there is a problem with the current route during evacuation, another shelter route is provided from the current location. Therefore, it is thought that the pedestrian route search evacuation system proposed in this paper will prevent accidents during evacuation.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.893-900
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• 2007

This paper suggests an algorithm that improves the disadvantages of the Dijkstra algorithm that is commonly used in GPS navigation system, searching for the shortest path. Dijkstra algorithm, first of all, requires much memory for the performance of the algorithm. It has to carry out number of node minus 1, since it determines the shortest path from all the nodes in the graph, starting from the first node. Therefore, Dijkstra algorithm might not be able to provide the information on every second, searching for the shortest path between the roads of the congested city and the destination. In order to solve these problems, this paper chooses a method of searching a number of nodes at once by means of choosing the shortest path of all the path nodes (select of minimum weight arc in-degree and out-degree), excluding the departure and destination nodes, and of choosing all the arcs that coincide with the shortest path of the path nodes, from all the node outgoing arcs starting from the departure node. On applying the suggested algorithm to 14 various digraphs, we succeeded to search the shortest path. In addition, the result was obtained at the speed of 2 to 3 times faster than that of Dijkstra algorithm, and the memory required was less than that of Dijkstra algorithm.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.51-67
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• 1996

The optimal path-finding problem becomes complicated when multiple variables are simultaneously considered such as physical route length, degree of congestion, traffic capacity of intersections, number of intersections and lanes, and existence of free ways. Therefore, many researchers in various fields (management science, computer science, applied mathematics, production planning, satellite launching) attempted to solve the problem by ignoring many variables for problem simplification, by developing intelligent algorithms, or by developing high-speed hardware. In this research, an integration of expert system technique and case-based reasoning in high level with a conventional algorithms in lower level was attempted to develop an optimal path-finding system. Early application of experienced driver's knowledge and case data accumulated in case base drastically reduces number of possible combinations of optimal paths by generating promising alternatives and by eliminating non-profitable alternatives. Then, employment of a conventional optimization algorithm provides faster search mechanisms than other methods such as bidirectional algorithm and $A^*$ algorithm. The conclusion obtained from repeated laboratory experiments with real traffic data in Seoul metropolitan area shows that the integrated approach to finding optimal paths with consideration of various real world constraints provides reasonable solution in a faster way than others.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.