• 제어로봇시스템학회논문지
• /
• 제17권8호
• /
• pp.824-832
• /
• 2011

An essential consideration to differentiate prosthetic hand from robot hand is its convenience and usefulness rather than high resolution or multi-function of the robot hand. Therefore, this study proposes a myoelectric hand with a 2 DOF auto wrist module which has 6 essential functions of the human hand such as open, grasp, pronation, supination, extension, flexion, which improves the convenience of the daily life. It consists of the 3 main parts, the myoelectric sensor for input signal without additional attachment to operate the prosthetic hand, hand mechanism with high-torqued auto-transmission mechanism and self-locking module which guarantee the safety under the abrupt emergency and minimum power consumption, and dual threshold based controller to make easy for adopting the multi-DOF myoelectric hand. We prove the validity of the proposed system with experimental results.

• Transactions on Control, Automation and Systems Engineering
• /
• 제3권4호
• /
• pp.236-241
• /
• 2001

Teach pendant is the most widely used means of robot teaching at present. Despite the difficulties of using the motion command buttons on the teach pendant, it is an economical, robust, and effective device for robot teaching task. This paper presents the development of a force/moment direction sensor named COSMO that can improve the teach pendant based robot teaching. Robot teaching experiment of a six axis commercial robot using the sensor is described where operator holds the sensor with a hand, and move the robot by pushing, pulling, and twisting the sensor in the direction of the desired motion. No prior knowledge of the coordinate system is required. The function of the COSMO sensor is to detect the presence f force and moment along the principal axes of the sensor coordinate system. The transducer used in the sensor is micro-switch, and this intuitive robot teaching can be implemented at a very low cost.

• 한국전자통신학회논문지
• /
• 제17권5호
• /
• pp.933-940
• /
• 2022

2차원 영상 센서를 이용하여 조종자의 3차원 손 위치를 인식하고 이를 기반으로 원격으로 6축 로봇팔을 제어하는 시스템을 개발하였다. 시스템은 물체의 영상정보를 인식하는 2차원 영상 센서 모듈, 영상정보를 로봇팔 제어 명령어로 전환하는 알고리즘, 자체 제작한 6축 로봇팔 및 제어 시스템으로 구성된다. 영상 센서는 조종자가 착용한 장갑의 모양과 색을 인지하여 크기 및 위치정보를 출력하게 되며, 본 연구에서는 이러한 위치 및 물체를 둘러싼 크기 정보를 이용하여 로봇 선단의 속도를 제어한다. 연구 방법의 검증은 자체 제작된 6축 로봇으로 실행하였으며, 조종자의 손동작 조종에 의한 실험을 통해 제안한 영상정보 제어 및 로봇 선단 제어 방법이 성공적으로 동작함을 확인하였다.

• 로봇학회논문지
• /
• 제13권4호
• /
• pp.265-271
• /
• 2018

The recent prosthetic technologies pursue to control multi-DOFs (degrees-of-freedom) hand and wrist. However, challenges such as high cost, wear-ability, and motion intent recognition for feedback control still remain for the use in daily living activities. The paper proposes a multi-channel knit band sensor to worn easily for surface EMG-based prosthetic control. The knitted electrodes were fabricated with conductive yarn, and the band except the electrodes are knitted using non-conductive yarn which has moisture wicking property. Two types of the knit bands are fabricated such as sixteen-electrodes for eight-channels and thirty-two electrodes for sixteen-channels. In order to substantiate the performance of the biopotential signal acquisition, several experiments are conducted. Signal to noise ratio (SNR) value of the knit band sensor was 18.48 dB. According to various forearm motions including hand and wrist, sixteen-channels EMG signals could be clearly distinguishable. In addition, the pattern recognition performance to control myoelectric prosthesis was verified in that overall classification accuracy of the RMS (root mean squares) filtered EMG signals (97.84%) was higher than that of the raw EMG signals (87.06%).

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제15권3호
• /
• pp.186-191
• /
• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• 한국항행학회논문지
• /
• 제13권4호
• /
• pp.503-508
• /
• 2009

본 논문에서는 특정인(장애인, 재활치료자, 고령자 등)들이 수월하게 컴퓨터를 사용 할 수 있도록 하기 위한 손동작 인식형 보조 입력장치를 설계하였다. 입력장치는 3차원 공간에서 손 동작 인식을 위해 자이로 센서를 사용하였고, 통신 대역은 무선 RF 2.4GHz 대역에서 신호를 송 수신 하도록 하였다. 제작된 보드는 자이로 모듈, RF 통신 모듈, MCU, USB 단자 등으로 구성되었다. 동작인식 실험결과, 마우스 기반의 커서 이동 및 프로그램 제어 등이 설계 규격대로 수행됨을 확인 하였다.

• 비파괴검사학회지
• /
• 제35권1호
• /
• pp.68-72
• /
• 2015

초음파 로봇 검사시스템은 발전설비 등 상시감시가 요구되는 구조물의 감시를 위해 연구와 개발이 활발히 진행되고 있다. 그러나 이러한 설비의 구조물은 형상과 구조가 매우 다양하고 복잡하여 단순한 패턴으로 이동과 검사가 가능한 로봇으로는 상시감시에 한계를 가지게 된다. 복잡한 구조물의 정밀검사는 정교한 행동이 가능한 로봇 시스템이 필요하다. 로봇의 제어를 초음파검사 작업자의 손의 형상에 따라 직관적으로 움직이도록 한다면 보다 정밀한 검사 로봇의 개발이 가능할 것으로 판단된다. 폴리머 굽힘센서는 대변형의 측정이 가능하고 곡면에 적용성이 높아 최근 인체 형상 측정 및 재활보조 등 다양한 활용을 위한 연구가 활발히 진행되고 있다. 본 연구에서는 구조물의 상시감시를 위한 초음파검사 로봇이 작업자의 손동작에 따라 동작이 가능한 직관적 제어를 위해 폴리머 굽힘센서를 이용하여 사람 손의 형상 감시 연구를 수행하였다. 다수의 센서를 적용하여 손의 다양한 움직임을 추정하고 실험적 검증을 통해 사람 손의 형상에 따른 직관적 로봇의 제어가 가능함을 확인하였다.

• 한국산학기술학회논문지
• /
• 제15권9호
• /
• pp.5440-5445
• /
• 2014

사람의 생체 신호를 측정하여 로봇 제어에 이용하는 연구는 최근까지 활발히 진행되고 있다. 하지만 정확한 센서 정보를 위한 복잡한 신호 처리가 필요하고 고가의 시스템을 필요로 하는 단점이 있다. 본 논문에서는 저가의 EMG 센서와 Flex 센서로부터 측정된 신호를 이용하여 사람의 손 동작을 인식한 후 해당 움직임을 원격지의 로봇 핸드로 구현하는 것을 목표로 한다. MCU(Micro Controller Unit) 와 해당 센서들을 이용하여 실험적으로 사람의 손과 팔 부근의 3개의 센서 부착 위치를 결정하고 움직임에 따른 출력 신호와 실제 동작 사이의 구분 방법을 결정한다. 동작 인식 정확도를 높이기 위해 MCU의 아날로그 기준 전압에 따른 디지털 값 변화 실험 수행 후 기준 전압을 3.3V로 선정하였다. 손 동작을 구현하기 위해 4개의 손가락과 손목부분으로 구성된 링크 구조의 로봇 핸드를 설계한 후 제작하였다. 결과적으로 간단한 센서와 저가의 MCU를 활용하여 원격지의 로봇 핸드를 제어할 수 있음을 보였다.

• 대한인간공학회지
• /
• 제31권4호
• /
• pp.551-556
• /
• 2012

Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

• 제어로봇시스템학회논문지
• /
• 제11권12호
• /
• pp.991-995
• /
• 2005

Sensor networks are the results of convergence of very important technologies such as wireless communication and micro electromechanical systems. In recent years, sensor networks found a wide applicability in various fields such as health, environment and habitat monitoring, military, etc. A very important step for these many applications is pattern classification and recognition of data collected by sensors installed or deployed in different ways. But, pattern classification and recognition are sometimes difficult to perform. Systematic approach to pattern classification based on modern teaming techniques like Multivariate Gaussian mixture models, can greatly simplify the process of developing and implementing real-time classification models. This paper proposes a new recognition system which is hierarchically composed of many sensor nodes haying the capability of simple processing and wireless communication. The proposed system is able to perform classification of sensed data using the Multivariate Gaussian function. In order to verify the usefulness of the proposed system, it was applied to hand gesture recognition system.