• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.1-10
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• 1996

There are many challenging problems in mobile robot navigation. As an example, a mobile robot may wander around in local minimum and may wiggle when it moves through a narrow corridor. In addition, the real time obstacle avoidance and the posture control of mobile robot are also very improtant problems. To address these problems, a navigation algorithm which is composed o freal time obstacle avoidance algorithm and a global path planner (GPP) that genrates the shortest path is presented. In this paper, the global path planner reduce the calculation time by reducing the dta to be handled. Also it can make a real time obstacle avoidance by using the fuzzy logic inference. So the presented algorithm provide a stable navigastion for the mobile robot when it fall into the unstable navigation.

• Korean Management Science Review
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• v.7 no.2
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• pp.51-57
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• 1990

The purpose of this thesis is to find the shortest path between two nodes on an acyclic network where the arc costs are determined by the starting time at the starting node of the arc. A branch and bound method for optimal solutions and a heuristic method is developed. In heuristic method Dijkstra algorithm is modified to maintain the minimum arrival times of maximum informations in the each time period at each node and is updated by the result with the insertion technique. Expermetal results among two methods are presented with regard to run time and solution qualities.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.88-92
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• 2018

Currently drone industry has become one of the fast growing markets and the technology for unmanned aerial vehicles are expected to continue to develop at a rapid rate. Especially small unmanned aerial vehicle systems have been designed and utilized for the various field with their own specific purposes. In these fields the path planning problem to find the shortest path between two oriented points is important. In this paper we introduce a path planning strategy for an autonomous flight of unmanned aerial vehicles through reinforcement learning with self-positioning technique. We perform Q-learning algorithm, a kind of reinforcement learning algorithm. At the same time, multi sensors of acceleraion sensor, gyro sensor, and magnetic are used to estimate the position. For the functional evaluation, the proposed method was simulated with virtual UAV environment and visualized the results. The flight history was based on a PX4 based drones system equipped with a smartphone.

• 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 for Quality Management
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• v.26 no.1
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• pp.192-200
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• 1998

The quickest path problem is one of the important things for quality of services in communication networks. It is to find a path to send a given amount of data from the source to the sink with minimum transmission time, where the transmission time is dependent on both the capacities and the traversal times of the arcs in the network. This is found under the networks that the capacity and the lead time of each ring are predetermined. It is general to solve the quickest path problem using shortest path algorithms. The relevant algorithms proposed till now are based on the capacity of rings in distributed environments. When the configuration of networks is changed, there can be two a, pp.oaches to find the quickest paths. The one is to find new quickest paths, and the other is to update the current quickest paths. As one of the algorithms for the latter, the distributed quickest path update algorithm was proposed. This paper aims to propose the distributed algorithm a, pp.icable to find the quickest path, when the configuration of networks is changed, using the quickest path tree update altorithm, and to verify its possibility of a, pp.ication by analyzing the transmission amount of data from one node to another from the theoretical point of view.

• Journal of KIISE:Information Networking
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• v.29 no.1
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• pp.57-64
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• 2002

Since most of the current route selection algorithms use the shortest path algorithm, network resources can not be efficiently used also traffics be concentrated on specific paths resulting in congestgion. In this paper we propose the statistical route selections(SRS) algorithm which adopts a statistical mechanism to utilize the network resource efficiently and to avoid congestion. The SRS algorithm handles requests on demand and chooses a path that meets the requested bandwidth. With the advent of the MPLS it becomes possible to establish an explicit LSP which can be used for traffic load balancing. The SRS algorithm finds a set of link utilizations for route selection, computes link weights using statistical mechanism and finds the shortest path from the weights. Our statistical mechanism computes the mean and the variance of link utilizations and selects a route such that it can reduce the variance and the number of congested links and increase the utilization of network resources. Throughout the simulation, we show that the SRS algorithm performs better than other route selection algorithms on several metrics like the number of connection setup failures and the number of congested links.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.19-31
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• 2016

A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

• Korean Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.33-44
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• 1996

This study deals with the development of wire path searching module as a part of automobile wire harness design system. Wire path searching module manages the free space, finds transition locations, and creates bundle paths to dramatically reduce a tedious iterative routing process which results in easy optimization of the bundle paths. A prime policy in the system configuration is to compromise between man's and computer's ability, and make it possible a designer's leading role in designing process. Human input is indispensable to cope with the special cases which were not considered in the initial design stage of the system. In this study, we improve the previous shortest-path-finding algorithm, (VGraph and RCA method) into a new method called Extended RCA. Bundles, connectors and transitions are handled as objects so one can manage and modify physical properties of the objects easily. Therefore a verification is allowed at any desired stage of design. The reuse of previous result is facilitated by using Dependency Structure, which represents the mutual relations among connectors, transitions, and bundles. Dependency Structure makes it possible the elimination of redundant calculating process, and consequently shorter routing time.

• Journal of the Ergonomics Society of Korea
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• v.24 no.2
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• pp.71-77
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• 2005

In spite of the importance of nuclear power as one of major electric energies in Korea, the nuclear safety has become the most serious social issue in the operation of the nuclear power plant. In this paper, a virtual work simulation program was developed to predict exposure dose during radiation work in radwaste storage. The work simulation program was developed. using $Java ^{TM}$applet and VRML-virtual reality modeling language. A numerical algorithm to find the optimal work path which minimize exposure dose during the given work, was developed and exposure dose on the optimal work path was compared with that on the shortest path. Comparing with the shortest path for the given work, the predicted optimal path consumed longer work time by II% but reduced total exposure dose by 46%. The simulation result showed that the exposure dose depended on not only work time, but also the distance between the worker and the radiation source. The developed simulation program could be a useful tool for the planning of radioactive waste work to increase the radiation safety of workers.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.541-551
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• 2021

Among the numerous duties of a librarian in a library, the work of arranging books is a job that the librarian has to do one by one. Thus, the cost of labor and time is large. In order to solve this problem, the interest in book-arranging robots based on artificial intelligence has recently increased. In this paper, we propose the K-ACO algorithm, which is the shortest path algorithm for multi-stops that can be applied to the library book arrangement robots. The proposed K-ACO algorithm assumes multiple robots rather than one robot. In addition, the K-ACO improves the ANT algorithm to create K clusters and provides the shortest path for each cluster. In this paper, the performance analysis of the proposed algorithm was carried out from the perspective of book arrangement time. The proposed algorithm, the K-ACO algorithm, was applied to a university library and compared with the current book arrangement algorithm. Through the simulation, we found that the proposed algorithm can allocate fairly, without biasing the work of arranging books, and ultimately significantly reduce the time to complete the entire work. Through the results of this study, we expect to improve quality services in the library by reducing the labor and time costs required for arranging books.