• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.381-381
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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 useful to detect the existence of a guideline. The wavelet transform is used to find the edge of guideline. Using wavelet transform, we can make an image processing more easily and rapidly. We make a fuzzy control rule using image data then make a decision the position and the navigation of the mobile robot. The center value that indicates the center of guideline is the input of fuzzy logic controller and the steering angle of the mobile robot is the fuzzy output. Some actual experiments for the mobile robot applied fuzzy control show that the mobile robot effectively moves to target position.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.895-897
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• 1995

As PLC has become cetral to today's FA environment, the importance of developing and providing special-unit of PLC such as Analog-unit, PID-unit, Fuzzy-unit has increased. In this paper introduce the Fuzzy-unit which is developed by LGIS R&D lab, and presents availability of PLC-control system with fuzzy-unit.

• 대한인간공학회지
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• 제20권2호
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• pp.29-46
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• 2001

This study is about the modeling of comfort feeling structure in indoor environments. To represent the degree of practical comfort feeling level in an environment, we measured elements of human sense and resultant elements of comfort feeling such as coziness, refreshment, and freshness with physical values(temperature, illumination, noise. etc.). The relationships of elements of human sense and elements of comfort feeling were formulated as a fuzzy model. And a hybrid-neural network with three layers were designed where obtained from fuzzy membership function values of the elements of human sense were used as inputs, and given as fuzzy membership function values of resultant elements of comfort feeling were used as outputs. Both kinds of fuzzy membership function values were obtained from physical values. The network was trained by measured data set. The proposed hybrid-neural network were tested and proposed a more realistic model of comfort feeling structure in indoor environments.

• 한국생산제조학회지
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• 제18권6호
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• pp.664-674
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• 2009

This paper presents the theoretical development of a complete navigation problem of a non-holonomic mobile robot by using sonar sensors. To solve this problem, a new method to compute a fuzzy perception of the environment is presented, dealing with the uncertainties and imprecision from the sensory system and taking into account nonholonomic constraints of the robot. Fuzzy perception, fuzzy controller are applied, both in the design of each reactive behavior and solving the problem of behavior combination, to implement a fuzzy behavior-based control architecture. Different experiments in populated environments have proved to be very successful. Our method is able to guide the mobile robot named KUM-Robo safety and efficiently during long experimental time.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.261-268
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• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• 로봇학회논문지
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• 제5권2호
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• pp.127-134
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• 2010

In this paper, a hybrid semi-3D path planning algorithm combining Virtual Tangential Vector(VTV) and fuzzy control is proposed. 3D dynamic environmental factors are reflected to the 2D path planning model, VTV. As a result, the robot can control direction from 2D path planning algorithm VTV and speed as well depending on the fuzzy inputs such as the distance between the robot and obstacle, roughness and slope. Performances and feasibilities of the suggested method are demonstrated by using Matlab simulations. Simulation results show that fuzzy rules and obstacle avoidance methods are working properly toward virtual 3D environments. The proposed hybrid semi-3D path planning is expected to be well applicable to a real life environment, considering its simplicity and realistic nature of the dynamic factors included.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1048-1052
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• 2004

The ubiquitous environment is to support people in their everyday life in an inconspicuous and unobtrusive way. This requires that information of the person and her preferences, liking, and habits are available in the ubiquitous system. In this paper, we propose the context aware system that can provide the tailored information service for user in ubiquitous computing environment. The system architecture is composed of 4 domain models that can perform some pre-defined tasks independently. And we suggest the hybrid algorithm combined with fuzzy and Bayesian network to reason what information is suitable for user environment. Finally, we apply to agent based RGA(Research Guide Assistant).

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.139-143
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• 2004

Lee et al have proposed a framework for the linguistic map-based navigational planning of a mobile robot on dynamic environment and provided simulation results applied it to the static environment[1], In this paper, we extends the navigational planning of a mobile robot into dynamic environment. There are two kinds of dynamic obstacles： (1) Time-obstacles that change condition of obstacles with time. (2) Space-obstacles that move their position with time. We propose an algorithm which a mobile robot identifies and avoids the two kinds of dynamic obstacles. The proposed algorithm consists of two stages： (1) The fuzzy logic-based perception stage which identifies the dynamic obstacles around a mobile robot by using sensory data and fuzzy rules, (2) The planning stage which plans the path to goal by avoiding the dynamic obstacles[2-6]. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제22권2호
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• pp.75-82
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• 2016

Visible light communication (VLC) using LED lamps is suitable for implementing an indoor positioning system in an indoor environment where the global positioning system (GPS) signal does not reach. In this paper, we present an indoor positioning system for mobile robots using a VLC beacon and fuzzy rules. This system consists of an autonomous mobile robot, VLC modules, and device application software. Fuzzy rules are applied to plan the global and local paths along which the mobile robot navigates indoors. The VLC transmitter modules are attached to the wall or the ceiling as beacons to transmit their own location information. The variable pulse position modulation (VPPM) algorithm is used to transmit data, which is a new modulation scheme for VLC providing a dimming control mechanism for flicker-free optical communication. The mobile robot has a receiver module to receive the location information while performing its mission in the environment where VLC transmitters are deployed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권4호
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• pp.305-314
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• 2015

The work presented in this paper deals with a navigation problem for multiple mobile robot system in unknown indoor environments. The environment is completely unknown for all the robots and the surrounding information should be detected by the proximity sensors installed on the robots' bodies. In order to guide all the robots to move along collision-free paths and reach the goal positions, a navigation method based on the combination of a set of primary strategies has been developed. The indoor environments usually contain convex and concave obstacles. In this work, a danger judgment strategy in accordance with the sensors' data is used for avoiding small convex obstacles or moving objects which include both dynamic obstacles and other robots. For big convex obstacles or concave ones, a wall following strategy is designed for dealing with these special situations. In this paper, a state memorizing strategy is also proposed for the "infinite repetition" or "dead cycle" situations. Finally, when there is no collision risk, the robots will be guided towards the targets according to a target positioning strategy. Most of these strategies are achieved by the means of fuzzy logic controllers and uniformly applied for every robot. The simulation experiments verified that the proposed method has a positive effectiveness for the navigation problem.