• 제목/요약/키워드: 로봇 손가락

검색결과 68건 처리시간 0.026초

근접 센서를 이용한 로봇 손의 파지 충격 개선 (Grasping Impact-Improvement of Robot Hands using Proximate Sensor)

  • 홍예선;진성무
    • 한국정밀공학회지
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    • 제16권1호통권94호
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    • pp.42-48
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    • 1999
  • A control method for a robot hand grasping a object in a partially unknown environment will be proposed, where a proximate sensor detecting the distance between the fingertip and object was used. Particularly, the finger joints were driven servo-pneumatically in this study. Based on the proximate sensor signal the finger motion controller could plan the grasping process divided in three phases ; fast aproach, slow transitional contact and contact force control. That is, the fingertip approached to the object with full speed, until the output signal of the proximate sensor began to change. Within the perating range of the proximate sensor, the finger joint was moved by a state-variable feedback position controller in order to obtain a smooth contact with the object. The contact force of fingertip was then controlled using the blocked-line pressure sensitivity of the flow control servovalve for finger joint control. In this way, the grasping impact could be reduced without reducing the object approaching speed. The performance of the proposed grasping method was experimentally compared with that of a open loop-controlled one.

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공압 구동식 로봇 손을 위한 소형 4/3-way 비례제어 밸브의 설계 및 실험 (Design and Experiment of a Miniature 4/3-Way Proportional Valve for a Servo-Pneumatic Robot Hand)

  • 류시복;홍예선
    • 한국정밀공학회지
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    • 제15권12호
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    • pp.142-147
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    • 1998
  • Developing robot hands with multi-degree-of-freedom is one of the topics that researchers have recently begun to improve the limitation by adding flexibility and dexterity. In this study, an articulated servo-pneumatic robot hand system with direct-drive joints has been developed whose main feature is the minimization of the dimension. The servo-pneumatic system is advantageous to fabricate a dexterous robot hand system due to the high torque-to-weight and torque-to-volume ratio. This enables the design of a finger joint with an integrated rotary vane type actuator which produces high output torque without reduction gears, being very robust. In order to control the servo-pneumatic finger joints, a miniature proportional valve that can be attached to the robot hand is required. In this paper, a flapper nozzle type 4/3-way proportional directional valve has been designed and tested. The experimental results show that the developed valve can control a finger joint satisfactorily without much vibratory joint movements and acoustic noises.

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강인한 손가락 끝 추출과 확장된 CAMSHIFT 알고리즘을 이용한 자연스러운 Human-Robot Interaction을 위한 손동작 인식 (A Robust Fingertip Extraction and Extended CAMSHIFT based Hand Gesture Recognition for Natural Human-like Human-Robot Interaction)

  • 이래경;안수용;오세영
    • 제어로봇시스템학회논문지
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    • 제18권4호
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    • pp.328-336
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    • 2012
  • In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

신체 힘에 의해 동작되는 부분 의수를 위한 부족구동 손가락 메커니즘 (Underactuated Finger Mechanism for Body-Powered Partial Prosthesis)

  • 윤덕찬;이건;최영진
    • 로봇학회논문지
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    • 제11권4호
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    • pp.193-204
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    • 2016
  • This paper presents an anthropomorphic finger prosthesis for amputees whose proximal phalanx is mutilated. The finger prosthesis to be proposed is able to make the amputees to perform the natural motion such as flexion/extension as well as self-adaptive grasping motion as if normal human finger does. The mechanism of finger prosthesis with three degrees-of-freedom (DOFs) consists of two five-bar and one four-bar linkages. Two passive components composed of torsional spring and mechanical stopper and only one active joint are employed in order to realize an underactuation. Each passive component is installed into the five-bar linkage. In order to activate the finger prosthesis, it is required for the user to flex and extend the remaining proximal phalanx on the metacarpophalangeal (MCP) joint, not an electric motor. Thus the finger prosthesis conducts not only the natural motion according to his/her intention but also the grasping motion through the deformation of springs by the object for human finger-like behavior. In order to reveal the operation principle of the proposed mechanism, kinematic analysis is performed for the linkage design. Finally both simulations and experiments are conducted in order to reveal the design feasibility of the proposed finger mechanism.

손가락 동작 분류를 위한 니트 데이터 글러브 시스템 (Knitted Data Glove System for Finger Motion Classification)

  • 이슬아;최유나;차광열;성민창;배지현;최영진
    • 로봇학회논문지
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    • 제15권3호
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    • pp.240-247
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    • 2020
  • This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.

2축 힘/모멘트센서를 이용한 원통형 손가락 힘측정장치 개발 및 특성평가 (Development of Cylindrical-type Finger Force Measuring System Using Two-axis Force/Moment Sensor and its Characteristic Evaluation)

  • 김갑순
    • 제어로봇시스템학회논문지
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    • 제17권5호
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    • pp.484-489
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    • 2011
  • Some patients can't use their hands because of inherent and acquired paralysis of their fingers. Their fingers can recover with rehabilitative training, and the extent of rehabilitation can be judged by grasping a cylindrical-object with their fingers. At present, the cylindrical-object used in hospitals is only a cylinder which cannot measure grasping force of the fingers. Therefore, doctors must judge the extent of rehabilitation by watching patients' fingers as they grasp the cylinder. A cylindrical-type finger force measuring system which can measure the grasping force of patients' fingers should be developed. This paper looks at the development of a cylindrical-type finger force measuring system with two-axis force/moment sensor which can measure grasping force. The two-axis force/moment sensor was designed and fabricated, and the high-speed force measuring device was designed and manufactured by using DSP (digital signal processing). Also, cylindrical-type finger force measuring system was developed using the developed two-axis force/moment sensor and the high-speed force measuring device, and the grasping force tests of men were performed using the developed system. The tests confirm that the average finger forces of right and left hands for men were about 186N and 172N respectively.

미지물체를 잡기 위한 로봇 손가락의 3축 힘감지센서 설계 및 제작 (Design and fabrication of robot′s finger 3-axis force sensor for grasping an unknown object)

  • 김갑순
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2002년도 춘계학술대회 논문집
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    • pp.229-232
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    • 2002
  • This paper describes the development of robot's finger 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously fur stably grasping an unknown object. In order to safely grasp an unknown object using the robot's fingers, they should detect the force of gripping direction and the force of gravity direction, and perform the force control using the detected farces. The 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously should be used for accurately detecting the weight of an unknown object of gravity direction. Thus, in this paper, robot's finger for stably grasping an unknown object is developed. And, the 3-axis farce sensor that detects the Fx, Fy, and Fz simultaneously fur constructing a robot's finger is newly modeled using several parallel-plate beams, and is fabricated. Also, it is calibrated, and evaluated.

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손가락 재활로봇의 5축 힘/모멘트센서를 이용한 손 누름제어 (Hand Pressing Control Using the Five-Axis Force/Moment Sensor of Finger Rehabilitation)

  • 김현민;김갑순
    • 센서학회지
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    • 제21권3호
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    • pp.192-197
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    • 2012
  • This paper describes the control of the hand fixing system attached to the finger rehabilitation robot for the rehabilitation exercise of patient's fingers. The finger rehabilitation robot is used to exercise the finger rehabilitation, and a patient's hand is safely fixed using the hand fixing system. In this paper, the hand fixing system was controlled with PD gains to fix a palm of the hand, and the characteristic test for the hand fixing system was carried out to sense the fixed hand movement of the front and the rear, that of the left and the right, and that of the upper. It is thought that the hand fixing system could safely fix the hand, and the movement of the fixed hand could be perceived using the five-axis force/moment sensor attached to the hand fixing system.

지능형 로봇손을 위한 손가락 힘센서 개발 (Development of Force Sensors for the Fingers of an Intelligent Robot's Hand)

  • 김갑순
    • 센서학회지
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    • 제23권2호
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    • pp.127-133
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    • 2014
  • This paper describes a design and manufacture of a two-axis force sensor and a single-axis force sensor for the fingers of an intelligent robot's hand. The robot's finger is composed of a two-axis force sensor, a first knuckle, a single-axis force sensor, a second knuckle, a spring, a motor of first knuckle, a motor of second knuckle, and so on. The two-axis force sensor attached to the first knuckle and the single-axis force sensor attached to the second knuckle were designed and manufactured, and the characteristics test of two sensors was carried out. As a test results, the interference error of the two-axis force sensor was less than 0.68%, the repeatability error of each sensor was less than 0.02%, and then the non-linearity was less than 0.03%. It is thought that the sensors can be used for the fingers of the intelligent robot's hand for rehabilitation exercise of finger patients.

직교형 손가락 재활로봇기구를 위한 힘센서 개발 및 특성실험 (Development of Force Sensors for Rectangular-Type Finger-Rehabilitation Robot Instruments and Their Characteristic Test)

  • 김갑순
    • 센서학회지
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    • 제21권2호
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    • pp.127-134
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    • 2012
  • Stroke patients must do the rehabilitation exercise to recover their fingers' function using a rehabilitation robot. But the rehabilitation robots mostly have not the force sensors to control the applied force to each finger. Thus, in this paper, the development of a force sensor for thumb rehabilitation robot and four two-axis force sensors for four-finger rehabilitation robot were developed. The force sensor and four two-axis force sensors could be used to measure the applied force to each finger, and the forces could be used to control the applied forces to each sensor in rehabilitation exercise using in the rehabilitation robot. The developed sensors have non-linearlity error of less than 0.05 %, repeatability error of less than 0.03 %, and the interference error of two-axis force sensor is less than 0.2 %.