• The Journal of Korea Robotics Society
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• v.14 no.2
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.215-216
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1405-1406
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.213-214
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• 2012

• The Journal of Korea Robotics Society
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• v.5 no.2
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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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.670-673
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• 2000

This paper attempt analysis and computer simulation of dynamics of a set of dual multi-joint fingers with soft-deformable tips which are grasping. Firstly, a set of differential equation describing dynamics of the fingers and object together with geometric constraint of tight area-contacts is formulated by Euler-Lagrange's formalism. Secondly, problems of controlling both the internal force and the rotation angle of the grasped object under the constraints of area-contacts of tight area-contacts are discussed. The effect of geometric constraints of area-contacts on motion of the overall system is analyzed and a method of computer simulation for overall system of differential-algebraic equations is presented. Finally, simulation results are shown and the effects of geometric constraints of area-contact is discussed.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.7
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• pp.753-761
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• 2012

This paper describes development of a hand and finger fixing system for the rehabilitation exercise of patient's fingers. In order to exercise the finger rehabilitation using a finger rehabilitation robot, a patient's hand or fingers are fixed safely. In this paper, The hand and fingers fixing system can safely fix stroke patient's hand and fingers by pressing with force control system. The characteristic test of the system was carried out. It is thought that the system could be used for fixing their fingers in stroke patient's finger rehabilitation exercise.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.703-709
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• 2015

In this work, a robot aimed at grapping and delivering an object by using a simple finger-pointing command from a hand- or arm-handicapped person is introduced. In this robot system, a Leap Motion sensor is utilized to obtain the finger-motion data of the user. In addition, a Kinect sensor is also used to measure the 3D (Three Dimensional)-position information of the desired object. Once the object is pointed at through the finger pointing of the handicapped user, the exact 3D information of the object is determined using an image processing technique and a coordinate transformation between the Leap Motion and Kinect sensors. It was found that the information obtained is transmitted to the robot controller, and that the robot eventually grabs the target and delivers it to the handicapped person successfully.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.360-365
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• 2003

In this paper, we have developed a general purpose motion controller using an FPGA(Field Programmable Gate Array). The multi-PID controllers on a single chip are implemented as a system-on-chip for multi-axis motion control. We also develop a PC GUI for an efficient interface control. Comparing with the commercial motion controller LM 629 it has multi-independent PID controllers so that it has several advantages such as space effectiveness, low cost and lower power consumption. In order to test the performance of the proposed controller, robot finger is controlled. The robot finger has three fingers with 2 joints each. Finger movements show that position tracking was very effective. Another experiment of balancing an inverted pendulum on a cart has been conducted to show the generality of the proposed FPGA PID controller. The controller has well maintained the balance of the pendulum.