• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1034-1041
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• 2014

This paper propose a fuzzy inference model for obstacle avoidance for a mobile robot with an active camera, which is intelligently searching the goal location in unknown environments using command fusion, based on situational command using an vision sensor. Instead of using "physical sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data. In this paper, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. We describe experimental results obtained with the proposed method that demonstrate successful navigation using real vision data.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.109-115
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• 2008

A lot of methods to improve the learning effect of learners in E-learning have been researched and applied. In roost E-learning systems, the learning navigation presenting the learning course and progress to learners is applied. But roost learning course and progress are designed by teacher beforehand and learners study the learning course and progress already fixed. In this research, a learning navigation which can change the learning course and progress dynamically according to learner's learning effect is presented. For this purpose, the factors which define the learning course and progress by learning chapters, contents and item difficulties were classified and each process logic was analyzed through CSP.

• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• ETRI Journal
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• v.42 no.3
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• pp.433-445
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• 2020

A denial-of-service (DoS) attack is a serious attack that targets web applications. According to Imperva, DoS attacks in the application layer comprise 60% of all the DoS attacks. Nowadays, attacks have grown into application- and business-layer attacks, and vulnerability-analysis tools are unable to detect business-layer vulnerabilities (logic-related vulnerabilities). This paper presents the business-layer dynamic application security tester (BLDAST) as a dynamic, black-box vulnerability-analysis approach to identify the business-logic vulnerabilities of a web application against DoS attacks. BLDAST evaluates the resiliency of web applications by detecting vulnerable business processes. The evaluation of six widely used web applications shows that BLDAST can detect the vulnerabilities with 100% accuracy. BLDAST detected 30 vulnerabilities in the selected web applications; more than half of the detected vulnerabilities were new and unknown. Furthermore, the precision of BLDAST for detecting the business processes is shown to be 94%, while the generated user navigation graph is improved by 62.8% because of the detection of similar web pages.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.222-228
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• 2003

A tool which can be used for the analysis of a robot soccer game is presented. The tool enables automatic filtering and selection of game sequences which are suitable for the analysis of the game. Fuzzy logic is used since the data gathered by a camera is highly noisy. The data used in the paper was recorded during the game Germany - Slovenia in Hagen, on November 11, 2001. The dynamic parameters of our robots are estimated using the least squares technique. Meandering parameters are estimated and an attempt is made to identify the strategy of the opposing team with the method of introspection.

• ETRI Journal
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• v.41 no.4
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• pp.506-514
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• 2019

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three-lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.105-112
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• 2014

The International Maritime Organization has determined that more than 80% of maritime accidents are caused by human error. A variety of methods have been considered to reduce maritime accidents caused by such human error. Navigators operate by observing surrounding maritime situations and analyzing information using various navigational devices. This study proposes a system to ensure safe navigation by assisting navigators through the delivery of maritime safety information (MSI) between land and sea. In the future, supplementing the system through long-term on-the-ship tests is necessary by defining MSI in relation to maritime service portfolio regions.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.55-60
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• 2006

지능형 로봇이 성장 동력 산업으로 선정되면서 국가적인 관심이 지능형 로봇산업에 모이고 있다. 지능형 로봇의 분야에서 있어 자율 이동 로봇에 관한 연구는 중요한 이슈가 되고 있다. 주어진 환경에서 환경을 인식하고, 얻어진 정보에 따라 효율적인 주행을 하기 위해 환경지도를 구성한다. 구성된 환경지도를 기반으로 목표지점을 향한 광역경로 계산을 수행하고, 얻어진 경로를 따라 이동함으로써 목표점에 이르게 된다. 본 논문에서는 퍼지 환경 지도를 제안하고, 퍼지 환경지도로부터 최단시간 광역 경로를 계산하는 알고리즘을 소개하며, 주행 제어를 위한 퍼지 제어기를 제안한다.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.195-200
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• 2000

This paper describes the path planning method in an unknown environment for an autonomous mobile robot equipped with CCD(Charge-Coupled Device) camera. The mobile robot moves along the guideline. The CCD camera is used for the detection of the existence of a guideline. The wavelet transform is used to find the edge of guideline. It is possible for us to do image processing more easily and rapidly by using wavelet transform. We make a fuzzy control rule using image data as an input then determined the position and the navigation of the mobile robot. The center value of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy controller output. Some actual experiments show that the mobile robot effectively moves to target position by means of the applied fuzzy control.

• Journal of the Korean Institute of Navigation
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• v.22 no.2
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• pp.47-52
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• 1998

Recently , there have been considerable researches about the fusion of fuzzy logic and neural networks. The propose of thise researches is to combine the advantages of both. After the function of approximation using GMDP (Generalized Multi-Denderite Product)neural network for defuzzification operation of fuzzy controller, a new fuzzy-neural network is proposed. Fuzzy membership function of the proposed fuzzy-neural network can be adjusted by learning in order to be adaptive to the variations of a parameter or the external environment. To show the applicability of the proposed fuzzy-nerual network, the proposed model is applied to a speed control o fDC sevo motor. By the hardware implementation, we obtained the desriable results.