• Journal of Korea Game Society
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• v.17 no.5
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• pp.123-132
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• 2017

The path-finding algorithm refers to an algorithm for navigating the route order from the current position to the destination in a virtual world in a game. The conventional path-finding algorithm performs graph search based on cost such as A-Star and Dijkstra. A-Star and Dijkstra require movable node and edge data in the world map, so it is difficult to apply online games with lots of map data. In this paper, we provide a Heuristic-based Genetic Algorithm Path-finding(HGAP) using Genetic Algorithm(GA). Genetic Algorithm is a path-finding algorithm applicable to game with variable environment and lots of map data. It seek solutions through mating, crossing, mutation and evolutionary operations without the map data. The proposed algorithm is based on Binary-Coded Genetic Algorithm and searches for a path by performing a heuristic operation that estimates a path to a destination to arrive at a destination more quickly.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1939-1944
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• 2003

This paper presents a global path planning algorithm based on a visibility graph method, and applies additionally various constraints for constructing the reduced visibility graph. The modification algorithm for generating the rounded path is applied to the globally shortest path of the visibility graph using the robot size constraint in order to avoid the obstacle. In order to check the visibility in given 3D map data, 3D CAD data with VRML format is projected to the 2D plane of the mobile robot, and the projected map is converted into an image for easy map analysis. The image processing are applied to this grid map for extracting the obstacles and the free space. Generally, the tree size of visibility graph is proportional to the factorial of the number of the corner points. In order to reduce the tree size and search the shortest path efficiently, the various constraints are proposed. After short paths that crosses the corner points of obstacles lists up, the shortest path among these paths is selected and it is modified to the combination of the line path and the arc path for the mobile robot to avoid the obstacles and follow the rounded path in the environment. The proposed path planning algorithm is applied to the mobile robot LCAR-III.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.55-61
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• 2021

As the demand for distance education increases, it is necessary to present a problem solving path through a learning tracking algorithm in order to support the efficient learning of learners. In this paper, we proposed a problem solving path of various difficulty levels in various subjects by supplementing the existing learning tracking algorithm. Through the data set obtained through the path for solving the learner's problem, the path through the prim's minimum Spanning tree was secured, and the optimal problem solving path through the recursive neural network was suggested through the path data set. As a result of the performance evaluation of the contents proposed in this paper, it was confirmed that more than 52% of the test subjects included the problem solving path suggested in the problem solving process, and the problem solving time was also improved by more than 45%.

• Journal of Mechanical Science and Technology
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• v.18 no.5
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• pp.753-761
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• 2004

In this paper, an efficient method for generating 5-axis cutting data for a turbine blade is presented. The interference elimination of 5-axis cutting currently is very complicated, and it takes up a lot of time. The proposed method can generate an interference-free tool path, within an allowance range. Generating the cutting data just point to the cutting process and using it to obtain NC data by calculating the feed rate, allows us to maintain the proper feed rate of the 5-axis machine. This paper includes the algorithms for: (1) CL data generation by detecting an interference-free heel angle, (2) finding the optimal tool path interval considering the cusp-height, (3) finding the adaptive feed rate values for each cutter path, and (4) the inverse kinematics depending on the structure of the 5-axis machine, for generating the NC data.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.1005-1014
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• 1990

This paper proposes the control unit of a 32-bit high-performance RISC type microprocessor. This control unit controls the whole data path of target processor and on chip instruction/data caches in 4-stage pipelined scheme. For the improvement of speed, large parts of data path and control unit are designed by domino-CMOS and hard-wired circuit technology. First, in this paper, target processor's instruction set and data path are defined, and next, all signals needed to control the data path are analyzed. The decoder of control unit and clock generated logic block are implemented in DCAL(Dynamic CMOS Array Logic) with modified clock scheme for the purpose of speed up and supporting RISC processor's pipelined architecture efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1615-1622
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• 2009

Generally, the Terminal Based Navigation System(TBNS) used embedded road data searches a path that has less qualitative than The Center Based Navigation System(CBNS). TBNS has not used real time road data but it is recently able to use it with technique such as TPEG. However, it causes to increase a cost of exploring by using real time road data for improvement quality of a path, because of limited performance. In this paper, we propose a Dynamic Heuristic to improve quality of path in the TBNS. Dynamic Heuristic(DH) is not fixed data and is dynamically modified using transferred real time road data from server. In this paper, we propose path-lading algorithm with Maximum Speed Dynamic Heuristic (DH-MAX) and do an experiment. The DH-MAX is to be used the highest speed as DH, in real map divided by same size. And proposed algorithm searches path using the priority searching only of the fixed data, but also the highest speed with real time information. In the performance test, the quality of path is enhanced but the cost of searching is increased than A* algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.327-333
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• 2022

Wireless Sensor Networks (WSNs) plays an important role in our everyday life. WSN is distributed in all the places. Nowadays WSN devices are developing our world as smart and easy to access and user-friendly. The sensor is connected to all the resources based on the uses of devices and the environment [1]. In WSN, Quality of Service is based on time synchronization and scheduling. Scheduling is important in WSN. The schedule is based on time synchronization. Min-Max data size scheduling is used in this proposed work. It is used to reduce the Delay & Energy. In this proposed work, Two-hop neighboring node is used to reduce energy consumption. Data Scheduling is used to identify the shortest path and transmit the data based on weightage. The data size is identified by three size of measurement Min, Max and Medium. The data transmission is based on time, energy, delivery, etc., the data are sent through the first level shortest path, then the data size medium, the second level shortest path is used to send the data, then the data size is small, it should be sent through the third level shortest path.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.7
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• pp.498-509
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• 1988

A BF(breadth-first) linear quadtree as a new data structure for image data is suggested, which enables us to compress the image data efficiently and to make operations of the compressed data easily. It is a list of path names for black nodes as the linear quadtree is. The path name for each black node of a BF linear quadtree is represented as a sequence of path codes from the root node to itself, whereas that of linear quadtree as a sequence of path codes from the root node to itself and fill characters for cut-offed path from it to any n-level node which corresponds to a pixel of an image. The BF linear quadtree provides a more efficent compression ratio than the linear quadtree does, because the former does not require redundant characters, fill characters, for the cut-offed paths. Several operations for image processing can be also implemented on this hierarchical structure efficiently, because it is composed of only the black nodes ad the linear quadtree is . In this paper, algorithms for several operations on the BF linear quadtree are defined and analyzed. Experimental results for forur image data are also given and discussed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.5
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• pp.379-387
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• 2019

The complexity of path planning for visiting multiple mission points is even larger than that of single pair path planning. Deciding a path for visiting n mission points requires conducting $n^2+n$ times of single pair path planning. We propose Multiple Mission $D^*$ Lite($MMD^*L$) which is an optimal path planning algorithm for visiting multiple mission points in dynamic environments. $MMD^*L$ reduces the complexity by reusing the computational data of preceding single pair path planning. Simulation results show that the complexity reduction is significant while its path optimality is not compromised.