• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.699-705
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• 2009

This paper is represented to research of driving control for the forklift AGV. The related works that were studied about AGV as heavy equipment used two methods which are magnet-gyro and wire guidance for localization. However, they have weaknesses that are high cost, difficult maintenance according to change of environment. In this paper, we develop localization system through sensor fusion with laser navigation system and encoder, gyro for robustness. Also we design driving controller using fuzzy and proportional control. It considers distance and angle difference between forklift AGV and pallet for engaging work. To analyze performance of the proposed control system, we experiment in same working condition over 10 times. In the results, the average error was presented with 54.16mm between simulation of control navigation and real control navigation. Consequently, experimental result shows that the performance of proposed control system is effective.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.149-159
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• 2019

Six sigma is an innovative management movement which provides improved business process by adapting the paradigm and the trend of market and customers. Suitable selection of six sigma project could highly reduce the costs, improve the quality, and enhance the customer satisfaction. There are existing studies on the selection of Six Sigma projects, but few studies have been conducted to select the correct project under an incomplete information environment. The purpose of this study is to propose the application of integrated MCDM techniques for correct project selection under incomplete information. The project selection process of six sigma involves four steps as follows: 1) determination of project selection criteria 2) calculation of relative importance of team member's competencies 3) assessment with project preference scale 4) finalization of ranking the projects. This study proposes the combination methods by applying group fuzzy Analytical Hierarchy Process (AHP), an easy defuzzified number of Trapezoidal Fuzzy Number (TrFN) and Grey Relational Analysis (GRA). Both of the weight of project selection criteria and the relative importance of team member's competencies can be evaluated by group fuzzy AHP. Project preferences are assessed by easy defuzzified scale of TrFN in case of incomplete information.)

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.696-704
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• 2011

In this paper, we propose a mobile robot navigation algorithm using data fusion of a monocular camera and ultrasonic sensors. Threshold values for binary image processing are generated by a fuzzy inference method using image data and data of ultrasonic sensors. Threshold value variations improve obstacle detection for mobile robot to move to the goal under poor illumination environments. Obstacles detected by data fusion of camera and ultrasonic sensors are expressed on the grid map and avoided using the circular planning algorithm. The performance of the proposed method is evaluated by experiments on the Pioneer 2-DX mobile robot in the indoor room with poor lights and a narrow corridor.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.120-129
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• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.183-188
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• 2014

With the rapid growth of the mobile computing and sensor technologies, various application techniques related to USN converged with other related technologies are actively disseminated recently. Most of these applications are aimed at the proper control and system monitoring using context information gathered through various sensors. But it is not easy to control and monitor the system precisely and flexibly since data generated by sensors are huge and variety. In this paper, we design and implement the fuzzy-logic based central control system in USN to provide the flexibility and preciseness with sensed data. The performance of the proposed system is evaluated by a simulation study in terms of consumed electric power on the test bed of USN based streetlight control system.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.20-26
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• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

• Journal of IKEEE
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• v.18 no.1
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• pp.57-63
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• 2014

This paper is to technically implement the sensing platform for Home-Wellness Robot. The self-Localization of indoor mobile robot is very important for the sophisticated trajectory control. In this paper, the robot's self-localization algorithm is designed by RF sensor network and fuzzy inference. The robot realizes its self-localization, using RFID sensors, through the collaboration algorithm which uses fuzzy inference for combining the strengths of triangulation and triangulation. For the triangulation self-Localization, RSSI is implemented. TOA method is used for realizing the triangulation self-localization. The final improved position is, through fuzzy inference, made by the fusion algorithm of the resultant coordinates from trilateration and triangulation in real time. In this paper, good performance of the proposed self-localization algorithm is confirmed through the results of a variety of experiments in the base of RFID sensor network and reader system.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.952-958
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• 1999

This paper presented the application of GAs as a means of finding optimal solutions over a parameter space in the controller design for a fuzzy control system. The performance can involve a weighted combination of various performance characteristics such as rise-time, settling-time, settling-time, overshoot. The results obtained here are compared with those for a traditional design obtained using the root-locus method. In contrast to traditional methods, the GA-based method does not require the usual mathematical processess or mathematical model of the system. In this paper, the Ga-based Fuzzy control system combining Fuzzy control theory with the GA, that is known to be very effective in the optimization problem, will be proposed The effectiveness of the proposed control system will be demonstrated by computer simulations using task tracking position system in stable and unstable linear systems. It is shown that the GA-based controller is better than the traditional controller used It stable and unstable linear systems.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.47-57
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• 2005

In this research, the main theme is the system integration of driving simulator and unmanned vehicle. The total system is composed of the mater system and the slave system. The master system has a cockpit system and the driving simulator. The slave system means an unmanned vehicle, which is composed of the actuator system the sensory system and the vision system. The communication system is composed of RS-232C serial communication system which combines the master system with the slave system. To integrate both systems, the signal classification and system characteristics considered DSP(Digital Signal Processing) filter is designed with signal sampling and measurement theory. In addition, to simulate the motion of tele-operated unmanned vehicle on the driving simulator, the classical washout algorithm is applied to this filter, because the unmanned vehicle does not have a limited working space, while the driving simulator has a narrow working space and it is difficult to cover all the motion of the unmanned vehicle. Because the classical washout algorithm has a defect of fixed high pass later, fuzzy logic is applied to reimburse it through an adaptive filter and scale factor for realistic motion generation on the driving simulator.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.369-378
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• 2024

The aim of this study is to conduct a comparative study on the sustainability of the public pension. While the mainstream view on the sustainability of the public pension presupposes financial sustainability, the original purpose of guaranteeing retirement income has been overlooked. The sustainability of the public pension needs to consider not only financial sustainability, but also various factors such as demographic structure, labor productivity, industrial structure, life cycle of working households, government spending on public pensions, economic growth, and social consensus. With this awareness of the problem, this study conducted a fuzzy set qualitative comparative study in 44 countries, including Korea. As a result of the analysis, it was found that Korea had high financial sustainability for a single year, but relatively low integration related to social consultation and public pension operation, and adequacy such as the degree of guarantee and linkage with other pension systems was also relatively low. The sustainability of the broader public pension should be emphasized not only for financial sustainability, but also for adequacy and integration.