• 제어로봇시스템학회논문지
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• 제6권5호
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• pp.404-414
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• 2000

This paper addresses the development of a 3-fingered humanoid robot hand system and a real-time grasp synthesis of multifingered robot hands to find grasp configurations which satisfy the force closure condition of arbitrary shaped objects. We propose a fast and efficient grasp synthesis algorithm for planar polygonal objects, which yields the contact locations on a given polygonal object to obtain a force closure grasp by the multifingered robot hand. For an optimum grasp and real-time computation, we develop the preference and the hibernation process and assign physical constraints of the humanoid hand to the motion of each finger. The preferences consist of each sublayer reflecting the primitive preference similar to the conditional behaviors of humans for given objectives and their arrangements are adjusted by the heuristics inspired from human's grasping behaviors. The proposed method reduces the computational time significantly at the sacrifice of global optimality, and enables the grasp posture to be changable within two-finger and three-finger grasps. The performance of the presented algorithm is evaluated via simulation studies to obtain the force-closure grasps of polygonal objects with fingertip grasps. The architecture suggested is verified through experimental implementation to our robot hand system by solving the 2- or 3-finger grasp synthesis.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 추계학술대회 논문집
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• pp.491-492
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• 2008

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 춘계학술대회 논문집
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• pp.751-752
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• 2008

• 로봇학회논문지
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• 제7권1호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2126-2131
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• 2005

Interactions of a humanoid with a human are important, when the humanoid is requested to provide people with human-friendly services in unknown or uncertain environment. Such interactions may require more complicated and human-like behaviors from the humanoid. In this work the arm motions of a human are discussed as the early stage of human motion imitation by a humanoid. A motion capture system is used to obtain human-friendly arm motions as references. However the captured motions may not be applied directly to the humanoid, since the differences in geometric or dynamics aspects as length, mass, degrees of freedom, and kinematics and dynamics capabilities exist between the humanoid and the human. To overcome this difficulty a method to adapt captured motions to a humanoid is developed. The geometric difference in the arm length is resolved by scaling the arm length of the humanoid with a constant. Using the scaled geometry of the humanoid the imitation of actor's arm motions is achieved by solving an inverse kinematics problem formulated using optimization. The errors between the captured trajectories of actor arms and the approximated trajectories of humanoid arms are minimized. Such dynamics capabilities of the joint motors as limits of joint position, velocity and acceleration are also imposed on the optimization problem. Two motions of one hand waiving and performing a statement in sign language are imitated by a humanoid through dynamics simulation.

• 한국정밀공학회지
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• 제23권7호
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• pp.67-75
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• 2006

One of challenging topics for humanoid hands is to modulate a human-like motion of humanoid fingers handling an object. To this end, recognizing the motion behavior of human fingers is very important aspect. Based on this concept, this paper identifies the .joint trajectories of human fingers for an operation of hand opening and closing, and specifies an empirical model that coordinates an inter-articular relationship of human fingers doing the given motion. It is expected that the inter-articular model presented in this paper is applicable for humanoid fingers to mimic the natural motion of human fingers.

• 센서학회지
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• 제16권3호
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• pp.211-219
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• 2007

This paper describes the development of 6-axis force/moment sensor for a humanoid robot. In order to walk on uneven terrain safely, the robot's foot should perceive the applied forces Fx, Fy, Fz and moments Mx, My, Mz to itself, and be controlled by the foot using the forces and moments. Also, in order to grasp unknown object safely, the robot's hand should perceive the weight of the object using the mounted 6-axis force/moment sensor to its wrist, and be controlled by the hand using the forces and moments. Therefore, 6-axis force/moment sensor should be necessary for a humanoid robot's hand and foot. In this paper, 6-axis force/moment sensor for a humanoid robot was developed using many PPBs (parallel plate-beams). The structure of the sensor was newly modeled, and the sensing element of the sensor was designed using theoretical analysis. Then, 6-axis force/moment sensor was fabricated by attaching strain-gages on the sensing elements, and the characteristic test of the developed sensor was carried out. The rated outputs from theoretical analysis agree well with the results from the experiments.

• 제어로봇시스템학회논문지
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• 제14권1호
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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.

• 로봇학회논문지
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• 제1권2호
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• pp.188-196
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• 2006

During the communication and interaction with a human using motions or gestures, a humanoid robot needs not only to look like a human but also to behave like a human to make sure the meanings of the motions or gestures. Among various human-like behaviors, arm motions of the humanoid robot are essential for the communication with people through motions. In this work, a mathematical representation for characterizing human arm motions is first proposed. The human arm motions are characterized by the elbow elevation angle which is determined using the position and orientation of human hands. That representation is mathematically obtained using an approximation tool, Response Surface Method (RSM). Then a method to generate human-like arm motions in real time using the proposed representation is presented. The proposed method was evaluated to generate human-like arm motions when the humanoid robot was asked to move its arms from a point to another point including the rotation of its hand. The example motion was performed using the KIST humanoid robot, MAHRU.

• 한국정밀공학회지
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• 제26권1호
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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.