• Journal of the Korean Society of Industry Convergence
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• v.16 no.4
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• pp.141-145
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• 2013

This paper is the development of industrial robotic hand system and the design methods of industrial robot hand that can mimic human fingers motion. In order to overcome problems incurred during the reduction of the mobility, this study focuses on analyzing human hand structure and finger movements from an anatomical point of view. As a result, distinctive features that improve the discovered stability in constraints for range of motion in the fingers is reflected in this design concept. A 4-bar Linkage is used in robot finger structure. Lastly, there were experiments to inspect the developed robot hands performance. The developed robot hand has many potential applications and can be in many different fields.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.1-8
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• 2012

A humanoid robot hand with one thumb and two fingers has been developed. Each finger has the specially designed compact joints, called "MEC Joint", which convert the rotation of a motor to the swing motion of a pendulum. The robot hand with the MEC Joints is compact and relatively light but strong enough to grasp objects in the same manner as human being does in daily activities. In this paper the kinematic model and the torque characteristics of the MEC Joint are presented and compared with the results of the dynamic simulation and the dynamometer test. The dynamic behavior of the thumb and two fingers with MEC Joints are also presented by computer simulation.

• 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 of Industry Convergence
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• v.18 no.4
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• pp.231-240
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• 2015

In this paper, it was presented to design and analyze the kinematics of grasping a rigid object by means of multi-degrees-of-freedom hand fingers. It is shown firstly that a set of kinematic equation describing dynamics system of the arm and object together with geometric constraint of tight area-contacts is formulated by Lagrange's equation. It has been presented secondly that the problems of controlling both the forces of pressing object and the rotation angle of the object under the geometric constraints are discussed. In this research, the control method for static stable grasping and enhancing dexterity in manipulating things is proposed. It is illustrated by computer simulation that the control system gives the performance improvement in the kinematic grasping of the hand fingers of robot.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.159-162
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• 2007

The inverse kinematics problem in robotics is an essential work for grasping and manipulation tasks by robotic and humanoid hands. In this paper, an intelligent neural learning scheme for solving such inverse kinematics of humanoid fingers is presented. Specifically, a multi-layered neural network is utilized for effective inverse kinematics, where a dynamic neural learning algorithm is employed. Also, a bio-mimetic feature of general human fingers is incorporated to the learning scheme. The usefulness of the proposed approach is verified by simulations.

• Journal of the Ergonomics Society of Korea
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• v.28 no.3
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• pp.1-6
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• 2009

Recently, importance of the rehabilitation of hand pathologies as well as the development of high-technology hand robot has been increased. The biomechanical model of hand is indispensable due to the difficulty of direct measurement of muscle forces and joint forces in hands. In this study, a three-dimensional biomechanical model of four fingers including three joints and ten muscles in each finger was developed and a mathematical relationship between neural commands and finger forces which represents the enslaving effect and the force deficit effect was proposed. When pressing a plate under the flexed posture, the muscle forces and the joint forces were predicted by the optimization technique. The results showed that the major activated muscles were flexion muscles (flexor digitorum profundus, radial interosseous, and ulnar interosseous). In addition, it was found that the antagonistic muscles were also activated rather than the previous models, which is more realistic phenomenon. The present model has considered the interaction among fingers, thus can be more powerful while developing a robot hand that can totally control the multiple fingers like human.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.568-577
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• 2000

In this paper for an object grasped by a robot hand to work in stiffness control domain we first investigate the number of fingers for successful stiffness modulation in the object operational space. Next we propose a new compliance control method for robot hands which consist of two steps. RIFDS(Resolved Inter-Finger Decoupling Solver) is to decompose the desired compliance characteristic specified in the op-erational space into the compliance characteristic in the fingertip space without inter-finger coupling and RIJDS(Resolved Inter-Joint Decoupling Solver) is to decompose the fingertip space without inter-finger coupling and RIJDS(Resolved inter-Joint Decoupling Solver) is to decompose the compliance characteristic in the finger-tip space into the compliance characteristic given in the joint space without inter-joint coupling. Based on the analysis results the finger structure should be biominetic in the sense that either kniematic redundancy or force redundancy are required to implement the proposed compliance control scheme, Five-bar fingered robot hands are used as an illustrative example to implement the proposed compliance control method. To show the effectiveness of the proposed compliance control method simulations are performed for two-fingered and three-fingered robot hands.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.333-338
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• 2009

This paper presents a task-based analysis on the number of independent robotic fingers required for compliant manipulations. Based on the stiffness relation between operational space and fingertip space of a multi-fingered object manipulating system, we describe a technique for modulation of the fingertip stiffness without inter-finger coupling so as to achieve the desired stiffness specified in the operational space. Thus, we provides a guide line how many fingers are basically required for successful multi-fingered compliant tasks. Consequently, this paper enables us to assign effectively the number of fingers for various compliant manipulations by robot hands.

• The Journal of Korea Robotics Society
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• v.9 no.4
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• pp.258-263
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• 2014

An adaptive robot hand (AR-Hand) has a stable grasp of different objects in unstructured environments. In this study, we propose an AR-Hand based on a tendon-driven mechanism which consists of 4 fingers and 12 DOFs. It weighs 0.5 kg and can grasp an object up to 1 kg. This hand based on the adaptive grasp mechanism is able to provide a stable grasp without a complex control algorithm or sensor system. The fingers are driven by simple tendon structures with each finger capable of adaptively grasping the objects. This paper presents a method to decide the joint stiffness. The adaptive grasping is verified by various grasping experiments involving objects with different shapes and sizes.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.217-226
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• 2006

Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.