• 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.

• 한국산업융합학회 논문집
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• 제17권1호
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• pp.21-26
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• 2014

The focus of this paper is the designing a flexible three fingered hand system with 16 D.O.F for dynamic manipulation with an intelligent controller, and to build a useful database for dynamic manipulation based on the experimental results. The weight of the hand module is only 0.7 kg, but flexible motion and powerful grasping are possible. To achieve such a dynamic motion in a robotic hand, we have developed a flexible fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. We used three fingers, which is the minimum number to achieve a stable grasp.

• 한국산업융합학회 논문집
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• 제20권3호
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• pp.233-243
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• 2017

This paper proposes a structure of direct-printed flexible tactile-sensor. These flexible tactile sensors are based on pressure-sensing materials that allow pressure to be measured according to resistance change that in turn results from changes in material size because of compressive force. The sensing material consists of a mixture of multi walled carbon nanotubes (MWCNTs) and TangoPlus, which gives it flexibility and elasticity. The tactile sensors used in this study were designed in the form of array structures composed of many lines so that single pressure points can be measured. To evaluate the performance of the flexible tactile sensor, we used specially designed signal-processing electronics and tactile sensors to experimentally verify the sensors' linearity. To test object grasp, tactile sensors were attached to the surface of the fingers of grippers with three degrees of freedom to measure the pressure changes that occur during object grasp. The results of these experiments indicate that the flexible tactile sensor-based robotic gripper can grasp objects and hold them in a stable manner.

• 한국공작기계학회논문집
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• 제17권6호
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• pp.71-76
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• 2008

The focus of this paper is the designing a flexible three fingered hand system with 16 D.O.F for dynamic manipulation with an intelligent controller, and to build a useful database for dynamic manipulation based on the experimental results. The weight of the hand module is only 0.7 kg, but flexible motion and powerful grasping are possible. To achieve such a dynamic motion in a robotic hand, we have developed a flexible fingered hand with a control system incorporating image recognition system in which we deal with the problems of not only accuracy and range of motion but also the flexibility of hand. The fingers are arranged so as to grasp both circular and prismatic objects. In order to achieve the light mechanism, we reduced the number of joints and fingers as much as possible. We used three fingers, which is the minimum number to achieve a stable grasp.