• Journal of Mechanical Science and Technology
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• 제16권6호
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• pp.762-769
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• 2002

This paper presents how effective it is to use many features for improving the speed and accuracy of visual servo systems. Some rank conditions which relate the image Jacobian to the control performance are derived. The focus is to describe that the accuracy of the camera position control in the world coordinate system is increased by utilizing redundant features in this paper. It is also proven that the accuracy is improved by increasing the number of features involved. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm robot manipulator made by Samsung Electronic Co. Ltd..

• Journal of Advanced Marine Engineering and Technology
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• 제40권5호
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• pp.437-446
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• 2016

Feature selection has become an essential technique to reduce the dimensionality of data sets. Many features are frequently irrelevant or redundant for the classification tasks. The purpose of feature selection is to select relevant features and remove irrelevant and redundant features. Applications of the feature selection range from text processing, face recognition, bioinformatics, speaker verification, and medical diagnosis to financial domains. In this study, we focus on filter methods based on information entropy : IG (Information Gain), FCBF (Fast Correlation Based Filter), and mRMR (minimum Redundancy Maximum Relevance). FCBF has the advantage of reducing computational burden by eliminating the redundant features that satisfy the condition of approximate Markov blanket. However, FCBF considers only the relevance between the feature and the class in order to select the best features, thus failing to take into consideration the interaction between features. In this paper, we propose an improved FCBF to overcome this shortcoming. We also perform a comparative study to evaluate the performance of the proposed method.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.294-303
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• 1999

To improve the visual servoing performance, several strategies were proposed in the past such as redundant feature points, using a point with different height and weighted selection of image features. The performance of these visual servoing methods depends on the configuration between the camera and object. And redundant feature points require much computation efforts. This paper proposes the visual servoing method based on the disturbance obsever, which compensates the upper off-diagonal component of image feature jacobian to be the null. The performance indices such as sensitivity for a measure of richness, sensitivity of the control to noise, and comtrollability are shown to be improved when the image feature Jacobian is given as a block diagonal matrix. Computer simulations are carried out for a UUMA560 robot and show some results to verify the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1650-1654
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• 2004

This paper presents how it is effective to use many features for improving the speed and the accuracy of the visual servo systems. Some rank conditions which relate the image Jacobian and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm Robot manipulator made in Samsung Electronic Co. Ltd.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.778-782
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• 2003

This paper presents how it is effective to use many features for improving the speed and the accuracy of the visual servo systems. Some rank conditions which relate the image Jacobian and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm Robot manipulator made in Samsung Electronic Co. Ltd.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2312-2314
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• 1998

To improve the visual servoing performance, several strategies were proposed in the past such as redundant feature points, using a point with different height and weighted selection of image features. The performance of these visual servoing methods depends on the configuration between the camera and object. And redundant feature points require much computation efforts. This paper proposes the visual servoing m based on the disturbance observer, which compe the upper off-diagonal component of image fe Jacobian to be null. The performance indices su sensitivity for a measure of richness, sensitiv the control to noise, and controllability are sho improved when the image feature Jacobian is giv a block diagonal matrix. Computer simulation carried out for a PUMA560 robot and show results to verify the effectiveness of the pro method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.296-300
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• 1992

This paper deals with a dual mode control system design for the starching work robot. From the feature of this work, the robot has redundant degree of freedom. In this paper, we try to split the whole movement the robot into a gross motion part ai. a fine motion part so as to achieve a good tracking performance. The preview learning control is applied to the gross motion part. The validity of the dual mode control architecture is demonstrated.

• 제어로봇시스템학회논문지
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• 제4권6호
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• pp.765-771
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• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• 말소리와 음성과학
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• 제8권1호
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• pp.25-36
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• 2016

Previous studies showed that the voice onset time (VOT) of aspirated and lenis stops has been merged, and post-stop fundamental frequency (F0) has emerged as a primary cue to distinguish the two stops in the younger generation and female speech. The purpose of this study is to demonstrate that VOT merger in aspirated and lenis stops occurs after an F0 difference between the two stops becomes stabilized. In other words, unless post-stop F0, which is a redundant feature, is fully developed, it is hard for VOT merger to happen. Females have got a stable F0 difference in stops earlier than males. Therefore, VOT merger could happen, and as a result, females could take the lead in changing from VOT to F0 in initial stops. This study also shows that speakers who acquired F0 as a primary cue use F0 to the full to distinguish lenis stops from two other stops (aspirated and fortis).

• Communications for Statistical Applications and Methods
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• 제17권1호
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• pp.17-27
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• 2010

분류분석에 사용되는 k-최근접이웃 분류기에 유전알고리즘을 적용하여 의미 있는 변수들과 이들에 대한 가중치 그리고 적절한 k를 동시에 선택하는 알고리즘을 제시하였다. 다양한 실제 자료에 대하여 기존의 여러 방법들과 교차타당성 방법을 통하여 비교한 결과 효과적인 것으로 나타났다.