• Proceedings of the KSR Conference
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• 2011.10a
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• pp.607-613
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• 2011

This paper reviews search methods of multiple reasonable paths to implement multimodal public transportation network of Seoul. Such a large scale multimodal public transportation network as Seoul, the computation time of path finding algorithm is a key and the result of path should reflect route choice behavior of public transportation passengers. Search method of alternative path is divided by removing path method and deviation path method. It analyzes previous researches based on the complexity of algorithm for large-scale network. Applying path finding algorithm in public transportation network, transfer and loop constraints must be included to be able to reflect real behavior. It constructs the generalized cost function based on the smart card data to reflect travel behavior of public transportation. To validate the availability of algorithm, experiments conducted with Seoul metropolitan public multimodal transportation network consisted with 22,109 nodes and 215,859 links by using the deviation path method, suitable for large-scale network.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.77-78
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• 2008

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.311-312
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• 2007

This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the Maklink graph method. At first, we produce the path of a mobile robot a the static environment. And then we find midpoints of each path using the Maklink graph. Finally the ant colony optimization algorithm is adopted to get a shortest path. In this paper, we prove the performance of the proposed algorithm is better than that of the Dijkstra algorithm through simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.869-874
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• 2004

The inverse kinematics of five-axis milling machines produce large errors near stationary points of the required surface. When the tool travels cross or around the point the rotation angles may jump considerably leading to unexpected deviations from the prescribed trajectories. We propose three new algorithms to repair the trajectories by adjusting the rotation angles in such a way that the kinematics error is minimized. Given the tool orientations and the inverse kinematics of the machine, we first eliminate the jumping angles exceeding ${\pi}$ by using the angle adjustment algorithm, leaving the jumps less than ${\pi}$ to be further optimized. Next, we propose to apply an angle switching algorithm to compute the rotations and identify an optimized sequence of rotations by the shortest path scheme. Further error reduction is accomplished by the angle insertion algorithm based an o special interpolation to obtain the required rotations near the singularity. We have verified the algorithms by five-axis milling machines, namely, MAHO600E at the CIM Lab of Asian Institute of Technology and HERMLE UWF902H at the CIM Lab of Kasetsart University.

• ETRI Journal
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• v.27 no.6
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• pp.733-746
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• 2005

In the context of multi-protocol label switching (MPLS) traffic engineering, this paper proposes a scalable constraintbased shortest path first (CSPF) routing algorithm with multiple QoS metrics. This algorithm, called the multiple constraint-based shortest path first (M_CSPF) algorithm, provides an optimal route for setting up a label switched path (LSP) that meets bandwidth and end-to-end delay constraints. In order to maximize the LSP accommodation probability, we propose a link weight computation algorithm to assign the link weight while taking into account the future traffic load and link interference and adopting the concept of a critical link from the minimum interference routing algorithm. In addition, we propose a bounded order assignment algorithm (BOAA) that assigns the appropriate order to the node and link, taking into account the delay constraint and hop count. In particular, BOAA is designed to achieve fast LSP route computation by pruning any portion of the network topology that exceeds the end-to-end delay constraint in the process of traversing the network topology. To clarify the M_CSPF and the existing CSPF routing algorithms, this paper evaluates them from the perspectives of network resource utilization efficiency, end-to-end quality, LSP rejection probability, and LSP route computation performance under various network topologies and conditions.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.243-254
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• 2016

This study has produced a checker of the shortest path search problem with a total of 19 questions as a web-based computer evaluation based on the 'TRAFFIC' questions of PISA 2012. It is because the computer has been settled as an indispensable and significant instrument in the process of solving the problems of everyday life and as a media that is underlying in assessment. Therefore, information gifted students should be able to solve the problem using the computer and give clear enough commands to the computer so that it can perform the procedure. In addition, since it is the age that the computational thinking is affecting every sectors, it should give students new educational stimuli. The relationship between the rate of correct answers and the time took to solve the problem through the shortest route search process showed a significant correlation the variable that affected the problem solving as the difficulty of the question rises due to the increase of nodes and edges turned out to be the node than the edge. It was revealed that information gifted students went through algorithmic thinking in the process of solving the shortest route search problem. And It could be confirmed cognitive characteristics of the information gifted students such as 'ability streamlining' and 'information structure memory'.

• Journal of Ocean Engineering and Technology
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• v.23 no.6
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• pp.67-70
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• 2009

Nesting and cutting path optimization have a great effect on the improvement of productivity in many industries such as shipbuilding, automotive, clothing, and so on. However, few researches have been carried out for the optimization of a cutting path algorithm. This study proposed a new method for cutting optimization using gravity center of cutting pieces and a genetic algorithm. The proposed method was tested for a sample plate including many different shapes of cutting pieces and compared to 2 other conventional methods. The test results showed that the new method had the shortest cutting path and the best effectiveness among the 3 methods.

• ETRI Journal
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• v.31 no.1
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• pp.31-41
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• 2009

Optical burst switching is a promising switching paradigm for the next IP-over-optical network backbones. However, its burst loss performance is greatly affected by burst contention. Several methods have been proposed to address this problem, some of them requiring the network to be flooded by frequent state dissemination signaling messages. In this work, we present a traffic engineering approach for path selection with the objective of minimizing contention using only topological information. The main idea is to balance the traffic across the network to reduce congestion without incurring link state dissemination protocol penalties. We propose and evaluate two path selection strategies that clearly outperform shortest path routing. The proposed path selection strategies can be used in combination with other contention resolution methods to achieve higher levels of performance and support the network reaching stability when it is pushed under stringent working conditions. Results show that the network connectivity is an important parameter to consider.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.171-179
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• 2013

The primary function of navigation system is to provide route search and road guidance for safe driving for drivers. However, the existing route search system provides a simple service that looks up the shortest route using a safe driving DB without considering different road characteristics for the safety of the drivers. In order to maintain the safe driving, rather than searching the shortest path, a navigation system, in which the danger areas and/or the dangerous time zones have been considered, is required. Therefore, in this paper we propose a strategy of searching a navigation path to avoid danger areas for safe driving by using the A* algorithm. In the strategy, when evaluating the path-specific fitness of the navigation nodes, different heuristic weights were assigned to different types of risk areas. In particular, we considered three kinds of danger areas, such as accident-prone sections where accidents occur frequently, school zones, and intersection regions, as well as the time slots when the probability of danger is high. From computer simulation, the results demonstrate that the proposed scheme can provide the way to avoid danger areas on the route searching and confirm the possibility of providing the actual service.

• The Journal of Korea Robotics Society
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• v.8 no.1
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• pp.43-50
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• 2013

$A^*$ algorithm is a global path generation algorithm, and typically create a path using only the distance information. Therefore along the path, a moving vehicle is usually not be considered by driving characteristics. Deceleration at the corner is one of the driving characteristics of the vehicle. In this paper, considering this characteristic, a new evaluation function based path algorithm is proposed to decrease the number of driving path corner, in order to reduce the driving cost, such as driving time, fuel consumption and so on. Also the potential field method is applied for driving of UGV, which is robust against static and dynamic obstacle environment during following the generated path of the mobile robot under. The driving time and path following test was occurred by experiments based on a pseudo UGV, mobile robot in downscaled UGV's maximum and driving speed in corner. The experiment results were confirmed that the driving time by the proposed algorithm was decreased comparing with the results from $A^*$ algorithm.