• 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 Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.90-96
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• 2011

Finding the critical path (or the longest path) on acyclic directed graphs, which is well-known as PERT/CPM, the ambiguity of each acr's length can be modeled as a range or an interval, in which the actual length of arc may realize. In this case, the min-max regret criterion, which is widely used in the decision making under uncertainty, can be applied to find the critical path minimizing the maximum regret in the worst case. Since the min-max regret critical path problem with the interval arc's lengths is known as NP-hard, this paper proposes a heuristic algorithm to diminish the maximum regret. Then the computational experiments shows the proposed algorithm contributes to the improvement of solution compared with the existing heuristic algorithms.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.49-55
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• 2017

Robots, games and life applications have been developed while computer areas are developed. Moreover, various applications have been utilized for various users including the early childhood. Recently, smart phones have been dramatically used by various users including early childhood. Many applications need to find a path from a starting point to destinations. For example, without using real maps, users can find the direct paths for the destinations in realtime. Specifically, path exploration in game programs is so important to have accurate results. Nowadays, with these techniques, diverse applications for educations of early childhood have been developed. To deal with the functions, necessity of efficient path search programs with high accuracy becomes much higher. In this paper, we design and develop a friendly maze program for early childhood based on a path searching algorithm. Basically, the path of lineal distance from a starting location to destination is considered. Moreover, weight values are calculated by considering heuristic weighted h(x). In our approach, A* algorithm searches the path considering weight values. Moreover, we utilize depth first search approach instead of breadth first search in order to reduce the search space. so it is proper to use A* algorithm in finding efficient paths although it is not optimized paths.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.5
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• pp.1-6
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• 1984

In this paper, many kinds of heuristic functions were discussed. It's important factor in the path finding algorithm to find an accurate estimator of distance from the goal. Any space for which an accurate estimator exists is a domain of its problem being solves. Only domains with inaccurate estimators are interesting, so this paper deals with these cases for which the efficient use of heuristic information is necessary, It has been productive to use a computational approach to the shortest path problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.147-150
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• 2008

The real road network is regarded as a grid, and the grid is divided by fixed-sized cells. The path-finding is composed of two step searching. First searching travels on the abstract graph which is composed of a set of psuedo vertexes and a set of psuedo edges that are created by real road network and fixed-sized cells. The result of the first searching is a psuedo path which is composed of a set of selected psuedo edges. The cells intersected with the psuedo path are called as valid cells. The second searching travels with $A^*$ algorithm on valid cells. As pruning search space by removing the invalid cells, it would be possible to reduce the cost of exploring on real road network. In this paper, we present the method of creating the abstract graph and propose a path-finding algorithm on the abstract graph for extracting search space before traveling on real road network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.2009-2018
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• 2001

This paper presents a region offsetting algorithm for tool-path generation. The proposed region offsetting algorithm is developed by expanding the 'PWID offset algorithm [Choi and Park, 1999]'designed to offset a simple polygon. The PWID offset algorithm has three important steps; 1) remove 'local invalid ranges'by invoking a PWID test, 2) construct a raw offset owe and 3) remove 'global invalid ranges'by finding self-intersections of the raw offset cure. To develop a region offsetting algorithm, we modified the PWID offset algorithm by expanding the concept of the 'global invalid range'in the third step. The time complexity of the proposed algorithm is approximately Ο(n), where n is the number of points, and it is free of numerical errors for practical purposes. The proposed algorithm has been implemented and tested with various real regions obtained by intersecting a sculptured surface with a plane.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.313-320
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• 2019

Nowadays, as the availability of tiny, low-cost microcomputer increases at a high level, mobile robots are experiencing remarkable enhancements in hardware design, software performance, and connectivity advancements. In order to control Turtlebot 2, several algorithms have been developed using the Robot Operating System(ROS). However, ROS requires to be run on a high-cost computer which increases the hardware cost and the power consumption to the robot. Therefore, design an algorithm based on low-cost hardware is the most innovative way to reduce the unnecessary costs of the hardware, to increase the performance, and to decrease the power consumed by the computer on the robot. In this paper, we present a path-finding algorithm for TurtleBot 2 based on low-cost hardware. We implemented the algorithm using Raspberry pi, Windows 10 IoT core, and RPLIDAR A2. Firstly, we used Raspberry pi as the alternative to the computer employed to handle ROS and to control the robot. Raspberry pi has the advantages of reducing the hardware cost and the energy consumed by the computer on the robot. Secondly, using RPLIDAR A2 and Windows 10 IoT core which is running on Raspberry pi, we implemented the path-finding algorithm which allows TurtleBot 2 to navigate from the starting point to the destination using the map of the area. In addition, we used C# and Universal Windows Platform to implement the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.168-177
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• 2008

Path finding is a key element in the navigation of a mobile robot. To find a path, robot should know their position exactly, since the position error exposes a robot to many dangerous conditions. It could make a robot move to a wrong direction so that it may have damage by collision by the surrounding obstacles. We propose a method obtaining an accurate robot position. The localization of a mobile robot in its working environment performs by using a vision system and Virtual Reality Modeling Language(VRML). The robot identifies landmarks located in the environment. An image processing and neural network pattern matching techniques have been applied to find location of the robot. After the self-positioning procedure, the 2-D scene of the vision is overlaid onto a VRML scene. This paper describes how to realize the self-positioning, and shows the overlay between the 2-D and VRML scenes. The suggested method defines a robot's path successfully. An experiment using the suggested algorithm apply to a mobile robot has been performed and the result shows a good path tracking.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.1-23
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• 2005

The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.654-659
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• 2007

This paper proposes the effective method for classifying the working spates and modelling the environments, when complex working environments of AGVS(Automated Guided Vehicle System) ate changed. And, we propose the shortest path searching algorithm using the A* algorithm of graph search method. Also, we propose the methods for finding each AGV's travel time of shortest path. Finally, a simple example is included for visualizing the feasibility of the proposed methods.