• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.3
• /
• pp.47-54
• /
• 1992

This paper presents an image processing method which emphasizes a certain perception feeling on a color image. A series of fuzzy image processing schemes are proposed, which transform an color image represented in the LCH coordinate system to the image with a certain perception feeling based on the rules and fuzzy inference. To obtain the rules, results of the sensory perception tests are applied to the quantification theory. The proposed schemes can be effectively utilized in the color copy system, since printed outputs possibly look better than originals.

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.2
• /
• pp.69-76
• /
• 2014

This paper proposes a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.18 no.6
• /
• pp.664-674
• /
• 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.

• Journal of the Ergonomics Society of Korea
• /
• v.17 no.3
• /
• pp.71-80
• /
• 1998

This study proposed a method to apply certain fuzzy-related Quality control concepts to design customer-oriented products considering user requirements and information starting with the product development stage. This approach showed how to define the importance level of design elements and how to Quantify complex subjective perception of products using the fuzzy linguistic rating method and quality function deployment concepts. Using this approach, various customer requirements could be interpreted and reflected on the early design phase of a new product. To validate the proposed method, an experiment was conducted for designing the shape of the beeper using 14 subjects and 10 commercial beeper products. Front area, width/length ratio, thickness, curve variance, weight, and display area were selected as design elements of the beeper. The results showed that among design elements, front area and weight are significantly related with the subjective perception of the products. Consequently, this study indicates that customer decision on product selection could be made by quantification of user perception for beeper products.

• Journal of the Korean Society of Industry Convergence
• /
• v.18 no.1
• /
• pp.30-36
• /
• 2015

This paper presents the theoretical development of a complete navigation problem of a nonholonomic mobile robot by using ultrasonic sensors. To solve this problem, a new method to computer a fuzzy perception of the environment is presented, dealing with the uncertainties and imprecision from the sensory system and taking into account nonholonomic constranits 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. The performance of the proposed obstacle avoidance robot controller in order to determine the exact dynamic system modeling system that uncertainty is difficult for nomadic controlled robot direction angle by ultrasonic sensors throughout controlled performance tests. In additionally, this study is an in different ways than the self-driving simulator in the development of ultrasonci sensors and unmanned remote control techniques used by the self-driving robot controlled driving through an unmanned remote controlled unmanned realize the performance of factory antomation.

• International Journal of Highway Engineering
• /
• v.17 no.5
• /
• pp.57-66
• /
• 2015

PURPOSES: Nighttime driving is very different from daytime driving because drivers must obtain nighttime sight-distances based on road lights and headlights. Unfortunately, nighttime driving conditions in Korea are far from ideal due to poor lighting and an insufficient number of road lights and inadequate operation and maintenance of delineators. This study is conducted to develop new standards for nighttime road visibility based on experiments of driver perception for nighttime visibility conditions. METHODS : In the study, perception level and satisfaction of nighttime visibility were investigated. A total of 60 drivers participated, including 34 older drivers and 31 young drivers. To evaluate driver perceptions of nighttime road visibility, fuzzy set theory was used because the conventional analysis methods for driver perception are limited in effectiveness for considering the characteristics of perception which are subjective and vague, and are generally expressed in terms of linguistic terminologies rather than numerical parameters. RESULTS : This study found that levels of nighttime visibility, as perceived by drivers, are remarkably similar to their satisfactions in different nighttime driving conditions with a log-function relationship. Older drivers evaluated unambiguously degree of nighttime visibility but evaluations by young drivers regarding it were unclear. CONCLUSIONS : A minimum value of brightness on roads was established as YUX 30, based on final analyzed results. In other words, road lights should be installed and operated to obtain more than YUX 30 brightness for the safety and comfort of nighttime driving.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.395-398
• /
• 1998

In this paper, a method for the improvement of learning speed and convergence rate was proposed applied it to physiological neural structure with the advantages of artificial neural networks and fuzzy theory to physiological neuron structure, To compare the proposed method with conventional the single layer perception algorithm, we applied these algorithms bit parity problem and pattern recognition containing noise. The simulation result indicated that our learning algorithm reduces the possibility of local minima more than the conventional single layer perception does. Furthermore we show that our learning algorithm guarantees the convergence.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.42.3-42
• /
• 2002

Fuzzy Neural Network (FNN) is a compulsory element in a voice-controlled machine due to its inherent capability of interpreting imprecise natural language commands. To control such a machine, user's perception of imprecise words is very important because the words' meaning is highly subjective. This paper presents a voice based controller centered on an adaptable FNN to capture the user's perception of imprecise words. Conversational interface of the machine facilitates the learning through interaction. The system consists of a dialog manager (DM), the conversational interface, a Knowledge base, which absorbs user's perception and acts as a replica of human understanding of imprecise words,...

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.943-946
• /
• 2008

Many works have been done to enable computer, as brain of robot, to learn color categorization, most of them rely on modeling of human color perception and mathematical complexities. This paper aims at developing the innate ability of the computer to learn the human-like color categorization.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.05a
• /
• pp.223-226
• /
• 2002

This Paper presents an interval type-2 fuzzy perceptron algorithm that is an extension of the type-1 fuzzy perceptron algorithm proposed in [1]. In our proposed method, the membership values for each Pattern vector are extended as interval type-2 fuzzy memberships by assigning uncertainty to the type-1 memberships. By doing so, the decision boundary obtained by interval type-2 fuzzy memberships can converge to a more desirable location than the boundary obtained by crisp and type-1 fuzzy perceptron methods. Experimental results are given to show the effectiveness of our method