• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.62-69
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• 2008

A specialized anthropomorphic robot hand which can be attached to the biped humanoid robot MAHRU-R in KIST, has been developed. This built-in type hand consists of three fingers and a thumb with total four DOF(Degrees of Freedom) where the finger mechanism is well designed for grasping typical objects stably in human's daily activities such as sphere and cylinder shaped objects. The restriction of possible motions and the limitation of grasping objects arising from the reduction of DOF can be overcome by reflecting a typical human finger's motion profile to the design procedure. As a result, the developed hand can imitate not only human hand's shape but also its motion in a compact and efficient manner. Also this novel robot hand can perform various human hand gestures naturally and grasp normal objects with both power and precision grasping capability.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.89-96
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• 2009

This paper describes the intelligent robot's hand with three finger sensors for a humanoid robot. In order to grasp an unknown object safely, the intelligent robot's hand should measure the mass of the object, and determine the grasping force using the mass, finally control the grasping force using the finger sensors and the controller. In this paper, the intelligent robot's hand for a humanoid robot was developed. First, the six-axis force/moment sensor was manufactured. second, three finger force sensors were designed and fabricated, third, the high-speed controller was manufactured using DSP(digital signal processor), finally, the characteristic test for determining a grasping force and for grasping an unknown object safely It is confirmed that the hand could grasp an unknown object safely.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.415-420
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• 2017

Underactuated prosthetic hands are relatively light and economical. In this work, an economical grasping force control system is proposed for underactuated prosthetic hands with adaptive grasp capability. The prosthetic hand is driven by a main cable based on a set of electromyography sensors on the forearm of a user. Part of the main cable tension related to grasping force is fed back to the user by a skin-mounted vibrator. The proper relationship between the grasping force and the vibrator drive voltage was established and prototype tests were performed on a group of users. Relatively accurate grasping force control was achieved with minimal training of users.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.712-715
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• 1997

In image jacobian based visual servoing, generally, inverse jacobian should be calculated by complicated coordinate transformations. These are required excessive computation and the singularity of the image jacobian should be considered. This paper presents a visual servoing to control the pose of the robotic manipulator for tracking and grasping 3-D moving object whose pose and motion parameters are unknown. Because the object is in motion tracking and grasping must be done on-line and the controller must have continuous learning ability. In order to estimate parameters of a moving object we use the kalman filter. And for tracking and grasping a moving object we use a fuzzy inference based reinforcement learning algorithm of dynamic recurrent neural networks. Computer simulation results are presented to demonstrate the performance of this visual servoing

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.876-882
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• 2010

Stroke patients can't use their hands because of the paralysis their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by measuring the pressing force to be contacted with two fingers (thumb and first finger, thumb and middle finger, thumb and ring finger, thumb and little finger). But, at present, the grasping finger force of two-finger can't be accurately measured, because there is not a proper finger-force measuring system. Therefore, doctors can't correctly judge the rehabilitating extent. So, the finger-force measuring system which can measure the grasping force of two-finger must be developed. In this paper, the finger-force measuring system with a three-axis force sensor which can measure the pressing force was developed. The three-axis force sensor was designed and fabricated, and the force measuring device was designed and manufactured using DSP (Digital Signal Processing). Also, the grasping force test of men was performed using the developed finger-force measuring system, it was confirmed that the grasping forces of men were different according to grasping methods.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.99-104
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• 2009

This article describes the analysis of stable grasping for multi-fingered robot. An analysis method of stable grasping, which is based on the three-dimensional acceleration convex polytope, is proposed. This method is derived from combining dynamic equations governing object motion and robot motion, force relationship and acceleration relationship between robot fingers and object's gravity center through contact condition, and constraint equations for satisfying no-slip conditions at every contact points. After mapping no-slip condition to torque space, we derived intersected region of given torque bounds and the mapped region in torque space so that the intersected region in torque space guarantees no excessive torque as well as no-slip at the contact points. The intersected region in torque space is mapped to an acceleration convex polytope corresponding to the maximum acceleration boundaries which can be exerted by the robot fingers under the given individual bounds of each joints torque and without causing slip at the contacts. As will be shown through the analysis and examples, the stable grasping depends on the joint driving torque limits, the posture and the mass of robot fingers, the configuration and the mass of an object, the grasp position, the friction coefficients between the object surface and finger end-effectors.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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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.

• Journal of muscle and joint health
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• v.23 no.3
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• pp.169-178
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• 2016

Purpose: The purpose of this study was to evaluate effects of a cognitive improvement program on cognition, activities of daily living (ADL), depression, life satisfaction, and grasping power in small groups. Methods: A nonequivalent control group pretest-posttest design was used. Participants were 127 elders who were never diagnosed with dementia and could read (experimental: 61, control: 66). The program was consisted of 8 sessions to improve vocabulary and writing skills and fine motor skills. Each session was applied once a week for 8 weeks. A group was consisted of less than five members. Results: Cognition (t=3.82, p<.001), depression (t=-2.24, p=.027), life satisfaction (t=2.25, p=.027), and grasping power (Rt: t=2.44, p=.016, Lt: t=2.63, p=.010) except ADL (t=-0.49, p=.622) were significantly increased in the experimental group after the cognitive improvement program compared to the control group. Conclusion: This study indicates that the cognitive improvement program was effective to improve cognition, depression, life satisfaction and grasping power. Further study is needed in order to identify continuous effects of this cognitive improvement program.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.81-88
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• 2005

This paper attempts to derive the dynamic model of handling tasks in finger robot which grasps stable and manipulates a rigid object with some dexterity. Firstly, a set of differential equation describing dynamics of the manipulators and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. Secondly, the roblems of controlling both the forces of pressing object and the rotation angle of the object under the geometric constraints are discussed. The effect of geometric constraints of area-contacts between the link's end-effector and the object is analyzed and the model based on the differential-algebraic equations is presented. In this paper, the control method for dynamic stable grasping and enhancing dexterity in manipulating things is proposed. It is illustrated by computer simulation and the experiment that the control system gives the performance improvement in the dynamic stable grasping and nimble manipulating of the dual fingers robot with soft tips.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.41.5-41
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• 2002

This paper presents a feature extraction algorithm for vision-based micromanipulation. In order to guarantee of the accurate micromanipulation, most of micromanipulation systems use vision sensor. Vision data from an optical microscope or high magnification lens have vast information, however, characteristics of micro image such as emphasized contour, texture, and noise are make it difficult to apply macro image processing algorithms to micro image. Grasping points extraction is very important task in micromanipulation because inaccurate grasping points can cause breakdown of micro gripper or miss of micro objects. To solve those problems and extract grasping points for micromanipulation...