• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.25-36
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• 1996

Conventional radial-basis-function networks and fuzzy systems have serious problems in dealing with the non1inea:r approximations on high-dimensional spaces due to the explosive increase of the number of hidden nodes or fuzzy IF-THEN rules. In order to avoid such problems, this paper proposes a tree-structured intelligent system in which semi-local basis functions form its basic elements, and develops a training algorithm for the proposed system based on the modified genetic algorithm and LMS rule. Theoretical analysis is performed on the approximation capability of the proposed system, together with experimental studies which demonstrate the effectiveness of the developed methodology.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.147-156
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• 2016

A modalized Łukasiewicz three-valued propositional logic will be proposed in this paper which there are three modalities [t]; [m]; [f] to represent the three values t; m; f; respectively. And a Gentzen-typed deduction system will be given so that the the system is sound and complete with respect to the Łukasiewicz three-valued semantics Ł$_3$, which are given in soundness theorem and completeness theorem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.27-34
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• 1996

GENIE is a learning-based engine for building intelligent systems. Learning in GENIE proceeds by incrementally modeling its human or technical environment using a neural network and a genetic algorithm. The neural network is used to represent the knowledge for solving a given task and has the ability to grow its structure. The genetic algorithm provides the neural network with training examples by actively exploring the example space of the problem. Integrated into the training examples by actively exploring the example space of the problem. Integrated into the GENIE system architecture, the genetic algorithm and the neural network build a virtually self-teaching autonomous learning system. This paper describes the structure of GENIE and its learning components. The performance is demonstrated on a robot learning problem. We also discuss the lessons learned from experiments with GENIE and point out further possibilities of effectively hybridizing genetic algorithms with neural networks and other softcomputing techniques.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.418-424
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• 2005

For the safety and cost reduction of the navigation in the sea, we need automatic and intelligent system for the ship. For the ship automation, we need a route planning based on GPS and the nautical chart. In this paper, we propose a route planning technique using point of contact of the obstacle and treecreation technique. The efficiency of the proposed technique is proved by comparing with A* search technique that is the most famous search technique for route planning from the optimal point of view.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.77-80
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• 1998

The theoretical foundations of simple genetic algorithm(SGA) are the Schema Theorem and the Building Block Hypothesis. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum in GA-hard problems and deceptive problems. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and cooperate each other. In this paper we show why the co-evolutionary algorithm works better than SGA in terms of an extended schema theorem. Also the experimental results show a co-evolutionary algorithm works well in optimization problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.695-700
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• 2001

We design the intelligent diagnosis system for deciding on operation of TMS Analysis in this paper. We propose the method to model the neuro-fuzzy model for diagnosing the operation state of analyzer by using input and output signals of TMS and Expert's experiment data. Validity of the proposed system is asserted by numerical simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.807-810
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• 2001

Election Weighting Machine is used an electronic scale which has many trouble because of broken load cells. In this paper, we propose an Intelligent Diagnosis System will for an electronic weighting machine using fuzzy logic. It s purpose be detect of the load cell s trouble. The electronic circuit of system, which call junction box , will be connected resistance in a series at circuit of Wheatstone Bridge for monitoring the condition of load cells.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.103-108
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• 2015

The electric utility has the responsibility of reducing the impact of peaks on electricity demand and related costs. Therefore, they have introduced Direct Load Control System (DLCS) to automate the external control of shedding customer load that it controls. Since the number of customer load participating in the DLC program are keep increasing, DLCS operators a re facing difficulty in monitoring and controlling customer load. The existing DLCS needs constant operator intervention, e.g., whenever the load is about to exceed a predefined amount, it needs operator's intervention to control the on/off status of the load. Therefore, DLCS operators need the state-of-the-art DLCS, which can control automatically the on/off status of the customer load without intervention as much as possible. This paper presents an intelligent DLCS using the active database. The proposed DLCS is applying the active database to DLCS which can avoid operator's intervention as much as possible. To demonstrate the validity of the proposed system, variable production rules and intelligent demand controller are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.354-360
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• 1998

In general, it is very difficult to find optimal fuzzy rules by experience when a system is dynamical and/or complex. Futhermore proper fuzzy partitioning is not deterministic and there is no unique solution. Therefore we propose a new design method of an optimal fuzzy logic controller, that is a co-evolutionary genetic algorithm finding optimal fuzzy rule and proper membership functions at the same time. We formalize the relation between fuzzy rules and membership functions in terms of fitness. We review the typical approaching methods to co-evolutionary genetic algorithms , and then classify them by fitness relation matrix. Applications of the proposed method to a path planning problem of autonomous mobile robots when moving objects exist are presented to demonstrate the performance and effectiveness of the method.