• 제목/요약/키워드: robot hand

검색결과 427건 처리시간 0.026초

Design of a Robot's Hand with Two 3-Axis Force Sensor for Grasping an Unknown Object

  • Kim, Gab-Soon
    • International Journal of Precision Engineering and Manufacturing
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    • 제4권3호
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    • pp.12-19
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    • 2003
  • This paper describes the design of a robot's hand with two fingers for stably grasping an unknown object, and the development of a 3-axis force sensor for which is necessary to constructing the robot's fingers. In order to safely grasp an unknown object using the robot's fingers, they should measure the forces in the gripping and in the gravity directions, and control the measured forces. The 3-axis force sensor should be used for accurately measuring the weight of an unknown object in the gravity direction. Thus, in this paper, the robot's hand with two fingers for stably grasping an unknown object is designed, and the 3-axis force sensor is newly modeled and fabricated using several parallel-plate beams.

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.

안정적 로봇 파지를 위한 인공신경망 (Artificial Neural Network for Stable Robotic Grasping)

  • 김기서;김동언;박진현;이장명
    • 로봇학회논문지
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    • 제14권2호
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    • pp.94-103
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    • 2019
  • The optimal grasping point of the object varies depending on the shape of the object, such as the weight, the material, the grasping contact with the robot hand, and the grasping force. In order to derive the optimal grasping points for each object by a three fingered robot hand, optimal point and posture have been derived based on the geometry of the object and the hand using the artificial neural network. The optimal grasping cost function has been derived by constructing the cost function based on the probability density function of the normal distribution. Considering the characteristics of the object and the robot hand, the optimum height and width have been set to grasp the object by the robot hand. The resultant force between the contact area of the robot finger and the object has been estimated from the grasping force of the robot finger and the gravitational force of the object. In addition to these, the geometrical and gravitational center points of the object have been considered in obtaining the optimum grasping position of the robot finger and the object using the artificial neural network. To show the effectiveness of the proposed algorithm, the friction cone for the stable grasping operation has been modeled through the grasping experiments.

렌즈왜곡효과를 보상하는 새로운 hand-eye 보정기법 (A New Hand-eye Calibration Technique to Compensate for the Lens Distortion Effect)

  • 정회범
    • 한국정밀공학회지
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    • 제19권1호
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    • pp.172-179
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    • 2002
  • In a robot/vision system, the vision sensor, typically a CCD array sensor, is mounted on the robot hand. The problem of determining the relationship between the camera frame and the robot hand frame is refered to as the hand-eye calibration. In the literature, various methods have been suggested to calibrate camera and for sensor registration. Recently, one-step approach which combines camera calibration and sensor registration is suggested by Horaud & Dornaika. In this approach, camera extrinsic parameters are not need to be determined at all configurations of robot. In this paper, by modifying the camera model and including the lens distortion effect in the perspective transformation matrix, a new one-step approach is proposed in the hand-eye calibration.

촉각센서를 갖는 인간형 로봇손의 개발: SKKU Hand II (Development of Anthropomorphic Robot Hand with Tactile Sensor: SKKU Hand II)

  • 최병준;이상헌;강성철;최혁렬
    • 제어로봇시스템학회논문지
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    • 제12권6호
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    • pp.594-599
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    • 2006
  • In this paper an anthropomorphic robot hand called SKKU Hand IIl is presented, which has a miniaturized fingertip tactile sensor. The thumb is designed as one part of the palm and multiplies the mobility of the palm. The fingertip tactile sensor, based on polyvinylidene fluoride (PVDF) and pressure variable resistor ink, is physically flexible enough to be deformed into any three-dimensional geometry. In order to detect incipient slip, a PVDF strip is arranged along the direction normal to the surface of the finger of the robot hand. Also, a thin flexible sensor to sense the static force as well as the contact location is fabricated into an arrayed type using pressure variable resistor ink. The driving circuits and the tactile sensing systems for the SKKU Hand II are embedded in the hand. Each driving circuit communicates with others using CAN protocol. SKKU Hand II is manufactured and its feasibility is validated through preliminary experiments.

인간형 다지 다관절 로봇 핸드의 개발 (Design and Control of Anthropomorphic Robot hand)

  • 천주영;최병준;채한상;문형필;최혁렬
    • 로봇학회논문지
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    • 제5권2호
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    • pp.102-109
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    • 2010
  • In this study, an anthropomorphic robot Hand, called "SKKU Hand III" is presented. The hand has thirteen DOF(Degree-Of-Freedom) and is designed based on the skeletal structure of the human hand. Each finger module(except thumb module) has three DOF and four joints with a saddle joint mechanism which has two DOF at the base joint. Two distal joints of the finger module are mechanically coupled by a timing belt and pulleys. The thumb module is composed of a finger module and an additional actuator, which makes it possible to realize the opposition between the thumb and the other fingers. In addition, the palm DOF of the human hand is mimicked with a spatial link mechanism between the index finger and the thumb. Thus, it can grasp objects more stably and more strongly. For the modularization of the robotic hand all the driving circuits are embedded in the hand, and only the communication lines supporting CAN protocol with DC power cable are given as an interface. Therefore, it is possible to apply it to any robot system the interface. To validate the feasibility of the SKKU Hand III, a series of the representative grasp experiments such as power, precision, intermediate grasp etc. are carried out with the object around us and its operation is demonstrated.

직렬 탄성 액츄에이터 기반의 로봇 손가락의 힘 제어 (Force Control of Robot Fingers using Series Elastic Actuators)

  • 이승엽;김병상;송재복;채수원
    • 제어로봇시스템학회논문지
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    • 제18권10호
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    • pp.964-969
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    • 2012
  • Robot hands capable of grasping or handling various objects are important for service robots to effectively aid humans. In particular, controlling a contact force and providing a compliant motion are essential when the hand is in contact with objects. Many dexterous robot hands equipped with force/torque sensors have been developed to perform force control, but they suffer from the complexity of control and high cost. In this paper, a low-cost robot hand based on SEA (Series Elastic Actuator), which is composed of compression spring, stretch sensor, and wire, is proposed. The grasping force can be estimated by measuring the compression length of spring, which would allow the hand to perform force control. A series of experimentations are carried out to verify the performance of force control of the proposed robot hand, and it is shown that it can successfully control the contact force without any additional force/torque sensors.

Navigation of a Mobile Robot Using the Hand Gesture Recognition

  • Kim, Il-Myung;Kim, Wan-Cheol;Yun, Jae-Mu;Jin, Tae-Seok;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.126.3-126
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    • 2001
  • A new method to govern the navigation of a mobile robot is proposed based on the following two procedures: one is to achieve vision information by using a 2 D-O-F camera as a communicating medium between a man and a mobile robot and the other is to analyze and to behave according to the recognized hand gesture commands. In the previous researches, mobile robots are passively to move through landmarks, beacons, etc. To incorporate various changes of situation, a new control system manages the dynamical navigation of a mobile robot. Moreover, without any generally used expensive equipments or complex algorithms for hand gesture recognition, a reliable hand gesture recognition system is efficiently implemented to convey the human commands to the mobile robot with a few constraints.

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주행 로봇을 위한 단일 카메라 영상에서 손든 자세 검출 알고리즘 (Hand Raising Pose Detection in the Images of a Single Camera for Mobile Robot)

  • 권기일
    • 로봇학회논문지
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    • 제10권4호
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    • pp.223-229
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    • 2015
  • This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

손 모양 인식을 이용한 모바일 로봇제어 (Mobile Robot Control using Hand Shape Recognition)

  • 김영래;김은이;장재식;박세현
    • 전자공학회논문지CI
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    • 제45권4호
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    • pp.34-40
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    • 2008
  • 본 논문에서는 손 모양 인식을 이용한 비전기반의 모바일 로봇제어 시스템을 제안한다. 손 모양을 인식하기 위해서는 움직이는 카메라로부터 정확한 손의 경계선을 추출하고 추적하는 것이 필요하다. 이를 위해 본 논문에서는 초기 윤곽선 위치 및 경계에 강건하고, 빠른 물체를 정확히 추적할 수 있는 mean shift를 이용한 활성 윤곽선 모델(ACM) 추적 방법을 개발하였다. 제안된 시스템은 손 검출기, 손 추적기, 손 모양 인식기, 로봇 제어기 4가지 모듈로 구성된다. 손 검출기는 영상에서 피부색 영역으로 정확한 모양을 손으로 추출한 이후 활성 윤곽선 모델(ACM) 과 mean shift를 사용하여 손 영역을 정확히 추적한다. 마지막으로 Hue 모멘트에 이용하여 손의 형태를 인식한다. 제안된 시스템의 적합성을 평가하기 위하여 2족 보행로봇 RCB-1에서 실험이 수행되었다. 실험 결과는 제안된 시스템의 효율성을 증명하였다.