• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.1-15
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• 2000

In this paper, an efficient system for finding answers to a given path algebra expression in a directed acylic graph is discussed more particulary, in a multimedia presentration graph. Path algebra expressions are formulated using revised versions of operators next and until of temporal logic, and the connected operator. To evaluate queries with path algebra expressions, the node code system is proposed. In the node code system, the nodes of a presentation graph are assigned binary codes (node codes) that are used to represent nodes and paths in a presentation graph. Using node codes makes it easy to find parent-child predecessor-sucessor relationships between nodes. A pair of node codes for connected nodes uniquely identifies a path, and allows efficient set-at-a-time evaluations of path algebra expressions. In this paper, the node code representation of nodes and paths in multimedia presentation graphs are provided. The efficient algorithms for the evaluation of queries with path algebra expressions are also provided.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.152-160
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• 2017

Recent studies on automatic parking have actively adopted the technology developed for mobile robots. Among them, the path planning scheme plans a route for a vehicle to reach a target parking position while satisfying the kinematic constraints of the vehicle. However, previous methods require a large amount of computation and/or cannot be easily applied to different environmental conditions. Therefore, there is a need for a path planning scheme that is fast, efficient, and versatile. In this study, we use a multi-dimensional path grid map to solve the above problem. This multi-dimensional path grid map contains a route which has taken a vehicle's kinematic constraints into account; it can be used with the $A^*$ algorithm to plan an efficient path. The proposed method was verified using Prescan which is a simulation program based on MATLAB. It is shown that the proposed scheme can successfully be applied to both parallel and vertical parking in an efficient manner.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.121-128
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• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.257-264
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• 2015

This paper proposes an adaptive RRT (Rapidly-exploring Random Tree) for path planning of high DOF multibody robotic system. For an efficient path planning in high-dimensional configuration space, the proposed algorithm adaptively selects the robot bodies depending on the complexity of path planning. Then, the RRT grows only using the DOFs corresponding with the selected bodies. Since the RRT is extended in the configuration space with adaptive dimensionality, the RRT can grow in the lower dimensional configuration space. Thus the adaptive RRT method executes a faster path planning and smaller DOF for a robot. We implement our algorithm for path planning of 19 DOF robot, AMIRO. The results from our simulations show that the adaptive RRT-based path planner is more efficient than the basic RRT-based path planner.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.297-306
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• 2000

An efficient method of constructing $textsc{k}$-minimal path sets to evaluate the reliability of a flow network is presented. The network is considered to be in a functioning state if it can transmit a maximum flow which is greater than or equal to a specified amount of flow, $textsc{k}$say, and a $textsc{k}$-minimal path set is a minimal set of branches that satisfies the given flow constraint. In this paper, under the assumption that minimal path sets of the network are known, we generate composite paths by adding only a minimal set of branches at each iteration to get $textsc{k}$-minimal path sets after possibly the fewest composition, and compute maximum flow of composite paths using only minimal path sets. Thereby we greatly reduce the possible occurrence of redundant composite paths throughout the process and efficiently compute the maximum flow of composite paths generated. Numerical examples illustrate the method.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1208-1211
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• 1996

In this paper, an efficient and robust robot path planning technique is discussed. Concentric Ripple Edge Evaluation and Progression( CREEP ) algorithm[1] has been elaborated and expanded to carry out 3-D path planning. Like the 2-D case, robot can always find a path, if one exists, in a densely cluttered, unknown and unstructured 3-D obstacle environment. 3-D space in which the robot is expected to navigate is modeled by stacking cubic cells. The generated path is resolution optimal once the terrain is fully explored by the robot or all the information about the terrain is given. Path planning times are significantly reduced by local path update. Accuracy and efficiency of wave propagation in CREEP algorithm are achieved by virtual concentric sphere wave propagation. Simulations in 2-D and 3-D spaces are performed and excellent results are demonstrated.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.259-268
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• 2011

A robot education system by emulation based on Web can be efficiently used for understanding concept of robot assembly practice and control mechanism of robot by control programming. It is important to predict the path of the line tracer robot which has to be decided by the robot. Shortest Path Algorithm is a well known algorithm which searches the most efficient path between the start node and the end node. There are two related typical algorithms. Dijkstra Algorithm searches the shortest path tree from a node to the rest of the other nodes. $A^*$ Algorithm searches the shortest paths among all nodes. The delay time caused by turning the direction of navigation for the line tracer robot at the crossroads can give big differences to the travel time of the robot. So we need an efficient path determine algorithm which can solve this problem. Thus, It is necessary to analyze the overhead of changing direction of robot at multi-linked node to determine the next direction for efficient routings. In this paper, we reflect the real delay time of directional changing from the real robot. A speed based Dijkstra algorithm is proposed and compared with the previous ones to analyze the performance.

• 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.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.49-56
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• 2011

This paper deals with a methodology for searching optimal route of hazard material (hazmat) vehicles. When we make a decision of hazmat optimal paths, there is a conflict between the public aspect which wants to minimize risk and the private aspect which has a goal of minimizing travel time. This paper presents Efficient Vector Labeling algorithm as a methodology for searching optimal path of hazmat transportation, which is intrinsically one of the multi-criteria decision making problems. The output of the presented algorithm is a set of Pareto optimal paths considering both risk and travel time at a time. Also, the proposed algorithm is able to identify non-dominated paths which are significantly different from each other in terms of links used. The proposed Efficient Vector Labeling algorithm are applied to test bed network and compared with the existing k-shortest path algorithm. Analysis of result shows that the proposed algorithm is more efficient and advantageous in searching reasonable alternative routes than the existing one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1722-1728
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• 2004

To discover a certificate path is a very important topic in the PKI with a lot of candidate paths. The certificate path discovery processing is executed via many verifications and as the number of verification times increases, the validity of the discovered path becomes high. The selection of the path with high validity provides high-speed certificate validation by reducing the number of repetition times of path discovery and validation processing. Otherwise, there is a problem that the speed and computation overheads are increased. In this paper, we propose an efficient certificate path discovery algorithm can make high the certificate validity with low overhead.