• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.47-53
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• 2018

Various types of robotic arms are being used for industrial purposes, particularly with the small production of multi-products, and the importance of the gripper, which can be used in industrial fields, is increasing. This study evaluated a variable stiffness mechanism gripper that can change the stiffness using the nonlinearity of a flexible material. A prototype of the gripper was fabricated and examined to confirm the change in stiffness. The previous gripper was unable to grip objects in some situations with three variable stiffness mechanism. In addition, these mechanisms were not balanced and rarely rotated when the object was gripped. Therefore, a new type of gripper was needed to solve this problem. Inspired by the movements of the human palm and Venus Flytrap, a new type of a variable stiffness soft robot hand was designed. The possibility of grasping could be increased by interlocking the palm folding mechanism by pulling the tendon attached to the variable stiffness mechanism. The soft robotic hand was used to grasp objects of various shapes and weights more stably than the previous variable stiffness mechanism gripper. This new variable stiffness soft robot hand can be used selectively depending on the application and environment to be used.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.35-43
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• 2012

The UGV is one of the special field robot developed for mine detection, surveillance and transportation. To achieve successfully the missions of the UGV, the accurate and reliable navigation data should be provided. This paper presents design and implementation of multi-sensor-based open architecture integrated navigation for localization of UGV. The presented architecture hierarchically classifies the integrated system into four layers and data communications between layers are based on the distributed object oriented middleware. The navigation manager determines the navigation mode with the QoS information of each navigation sensor and the integrated filter performs the navigation mode-based data fusion in the filtering process. Also, all navigation variables including the filter parameters and QoS of navigation data can be modified in GUI and consequently, the user can operate the integrated navigation system more usefully. The conventional GPS/INS integrated system does not guarantee the long-term reliability of localization when GPS solution is not available by signal blockage and intentional jamming in outdoor environment. The presented integration algorithm, however, based on the adaptive federated filter structure with FDI algorithm can integrate effectively the output of multi-sensor such as 3D LADAR, vision, odometer, magnetic compass and zero velocity to enhance the accuracy of localization result in the case that GPS is unavailable. The field test was carried out with the UGV and the test results show that the presented integrated navigation system can provide more robust and accurate localization performance than the conventional GPS/INS integrated system in outdoor environments.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.34-39
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• 2009

As a subjective recognition effect, human's emotion has impulsive characteristic and it expresses intentions and needs unconsciously. These are pregnant with information of the context about the ubiquitous computing environment or intelligent robot systems users. Such indicators which can aware the user's emotion are facial image, voice signal, biological signal spectrum and so on. In this paper, we generate the each result of facial and voice emotion recognition by using facial image and voice for the increasing convenience and efficiency of the emotion recognition. Also, we extract the feature which is the best fit information based on image and sound to upgrade emotion recognition rate and implement Multi-Modal Emotion recognition system based on feature fusion. Eventually, we propose the possibility of the ubiquitous computing service reasoning method based on Bayesian Network and ubiquitous context scenario in the ubiquitous computing environment by using result of emotion recognition.

• Journal of the Korean Society for Precision Engineering
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• v.5 no.3
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• pp.20-30
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• 1988

Using the design parameters of multi-joint manipulator, worspace of the manipulator were evaluated analytically, and the relation between such design parameters and nonlinearity of the manipulator were presented dynamically. The ratio of the volumes of a manipulator's workspace to the cube of its total link length presents a kinematic performance index [NVI] for the manipullator. It is possible to geometrically represent the manipulator dynamics with the generalized inertia ellipsoid (GIE). The relation between the GIE configuration and the characteristics of manipulator dynamics was analysed in terms of inertia and nonlinear forces (Coliolis and centrifugal forces). The nonlinearity caused by the change of the GIE configuration were affected by the difference between the major and minor axes length of the GIE. The results of this investigationare applied to the optimal design of the manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1817-1822
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• 1991

A method of reducing overhead caused by the processor synchronization process and common memory accesses in finely grained tasks is described. We propose a scheduler which considers the preparation time during searching to minimize the redundant accesses to shared memory. Since the suggested hardware (synchronizer) determines the access order of processors and bus arbitration simultaneously by including the synchronization process into the bus arbitration process, the synchronization time vanishes. Therefore this synchronizer has no overhead caused by the processor synchronization[l]. The proposed scheduler algorithm is processed in parallel. The processes share the upper bound derived by each searching and the lower bound function is built considering the preparation time in order to eliminate as many searches as possible. An application of the proposed method to a multi-DSP system to calculate inverse dynamics for robot arms, showed that the sampling time can be twice shorter than that of the conventional one.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.591-594
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• 2003

In this paper, we propose a method to avoidance obstacle in which we assume that obstacle has an unstable limit cycle in the chaos trajectory surface. In order to avoid the obstacle, we assume that all obstacles in the chaos trajectory surface in which has an unstable limit cycle with Van der Pol equation. In this paper show also that computer simulation results are satisfy to avoid obstacle in the chaos trajectory with Chua's circuit equation of one or multi obstacle has an limit cycle with Van der Pol (VDP) efuation and compare to rate of cover in one robot which have random walk and Chua's equation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.59-62
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• 2017

본 논문에서는 평균 밝기 부분에 가중치 맵으로써 감마 변환에 기반한 선형 결합을 제안하고자 한다. 기존의 패치를 기반으로 한 가중치 맵은 평균 밝기 부분에서 영상 내 밝기 값이 한쪽으로 치우쳐 영상의 밝은 부분이 과포화 상태가 되어 세부 정보가 손실되는 단점이 있다. 이에 본 논문에서는 전역적 및 지역적 영상의 평균 밝기 값을 이용하여 감마 변환된 값을 선형 결합 시켜줌으로써 영역 내 세부 정보를 보존시키고 주관적 화질을 향상시켰다. 실험을 통해 결과를 분석하고 성능을 비교하여 기존 알고리듬에 비해 제안한 알고리듬이 우수함을 증명하였다.

• Journal of the korean Society of Automotive Engineers
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• v.3 no.1
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• pp.19-26
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• 1981

자동차제조에 있어서의 용접은 신뢰성 양산과 생력화에 대응하여 접합 조립하는 방법으로 특이한 분야를 형성하여 발전되었다. 예를 들면, 자동차의 생산은 기본적으로 양산체제를 갖추고 있 어서, 일반적으로 노동집약형 산업이라고 불리어지며 그 제조공정을 보면 stamping press 공정과 같이 용접공정도 비교적 장치산업적인 분야로 빠르게 자동화나 성인화 내지 무인화로 진행되고 있다. 자동차용접은 사람이 portable spot welder로 한점씩 용접하지만 양산에 대비한 합리화와 안정화를 위하여 다점용접 (multi spot weld)라는 자동화공법의 도입이 불가피하며 금일의 자 동차생산에 있어서 상식화가 되고 있다. 이것은 한개의 차체라면 차형의 대조 또는 press panel의 수에 따라 차이가 조금 있으나 약 4-5 천점의 점용접이 필요하기 때문에 여러 가지 반송장치와 조합하여 대규모의 line설비로 발전되어 가고 있다. 이와 같이 용접공정의 자동화는 생산성을 높이는 반면에 전용성이 높기 때문에 설계변경에 대한 초기투자의 용접설비 대부분을 갱신하여야 하는 새로운 투자의 필요문제가 증대되었다. 이러한 전용설비에 대한 유연성을 가미한 자동차로 지향되어, 그 한 방법으로 산업용 robot가 도입되었다. 근래에 와서는 자동차제조에 있어서 새 로운 용접기술을 합리적으로 효과있게 적용하는 기술이 금후의 연구과제라 하겠다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.