• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.229-232
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• 2002

This paper describes the development of robot's finger 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously fur stably grasping an unknown object. In order to safely grasp an unknown object using the robot's fingers, they should detect the force of gripping direction and the force of gravity direction, and perform the force control using the detected farces. The 3-axis force sensor that detects the Fx, Fy, and Fz simultaneously should be used for accurately detecting the weight of an unknown object of gravity direction. Thus, in this paper, robot's finger for stably grasping an unknown object is developed. And, the 3-axis farce sensor that detects the Fx, Fy, and Fz simultaneously fur constructing a robot's finger is newly modeled using several parallel-plate beams, and is fabricated. Also, it is calibrated, and evaluated.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.12-19
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• 2003

This paper describes the design of a robot's hand with two fingers for stably grasping an unknown object, and the development of a 3-axis force sensor for which is necessary to constructing the robot's fingers. In order to safely grasp an unknown object using the robot's fingers, they should measure the forces in the gripping and in the gravity directions, and control the measured forces. The 3-axis force sensor should be used for accurately measuring the weight of an unknown object in the gravity direction. Thus, in this paper, the robot's hand with two fingers for stably grasping an unknown object is designed, and the 3-axis force sensor is newly modeled and fabricated using several parallel-plate beams.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2711-2722
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• 1993

Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.105-113
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• 2003

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously, for stably grasping an unknown object. In order to safely grasp an unknown object using the robot's gripper, it should measure the force in the gripping direction and the force in the gravity direction, and perform the force control using the measured forces. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of made sensor was performed. and the result shows that interference errors of the developed sensor are less than 3%. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object was performed using it. The fabricated gripper could grasp an unknown object stably. Thus, the developed 6-axis robot's finger force/moment sensor may be used for robot's gripper.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.768-771
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• 1997

Geometric probing addresses the problem of determining geometric aspects of a structure from the mathematics and results of a physical measuring device such as a probe. This paper presents a new algorithm to recognize the shape of an unknown object by using a robot hand with a force and torque sensor. The new algorithm is called S.E.P.(Shape Exploration Procedure) which finds the global shape of an unknown object. The proposed method is composed of three major parts, finding contact informations such as contact point, calculation of shape information such as curvature, and expression of global shape from these informations. Comparing with the conventional approaches, the advantages of the proposed method are explained and verified by conducting experiments with a 3-dof SCARA robot.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.188-200
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• 2005

Control of a multi-fingered robotic hand is usually based on the theoretical analysis for kinematics and dynamics of fingers and of object. However, the implementation of such analyses to robotic hands is difficult because of errors and uncertainties in the real situations. This article presents the control method for estimating the kinematic constraint of an unknown object by active sensing. The experimental system has a two-fingered robotic hand suspended vertically for manipulation in the vertical plane. The fingers with three degrees-of-freedom are driven by wires directly connected to voice-coil motors without reduction gears. The fingers are equipped with three-axis force sensors and with dynamic tactile sensors that detect slippage between the fingertip surfaces and the object. In order to make an accurate estimation for the kinematic constraint of the unknown object, i.e. the constraint direction and the constraint center, four kinds of the active sensing and feedback control algorithm were developed: two position-based algorithms and two force-based algorithms. Furthermore, the compound and effective algorithm was also developed by combining two algorithms. Force sensors are mainly used to adapt errors and uncertainties encountered during the constraint estimation. Several experimental results involving the motion of lifting a finger off an unknown object are presented.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.411-416
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• 2006

This paper describes the development of a 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot's hand. In order to safely grasp an unknown object, robot's hand should measure the weight of an object and the force of grasping direction simultaneous. But, in the published papers, the grippers and hands equippd with the force sensor that could only measure the force of grasping direction, and grasped objects using their sensors. These grippers and hands can't safely grasp unknown objects, because they can't measure the weight of it. Thus, it is necessary to develop 3-axis force sensor that can measure the weight of an object and the force of grasping direction for an intelligent gripper. In this paper, 3-axis finger force sensor to grasp an unknown object safely in an intelligent robot's hand was developed. In order to fabricate a 3-axis finger force sensor, the sensing elements were modeled using parallel plate beams, and the theoretical analysis was performed to determine the size of sensing elements, then the 3-axis finger force sensor was fabricated. Also, the characteristic test of the developed 3-axis finger force sensor was performed.

• International Journal of Precision Engineering and Manufacturing
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• v.5 no.3
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• pp.54-61
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• 2004

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces $F_x$(x-direction force), $F_y$and $F_z$, and moments $M_x$ (x-direction moment), $M_y$ and $M_z$ simultaneously, for stable grasping of an unknown object. In order to safely grasp an unknown object using the robot's gripper, the force in the gripping direction and the force in the gravity direction should be measured, and the force control should be performed using the measured forces. Also, the moments $M_x$, $M_y$ and $M_z$ to accurately perceive the position of the object in the grippers should be detected. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of the fabricated sensor was performed, and the result shows that interference errors of the developed sensor are less than 3%. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object using the sensors was performed using it. The fabricated gripper could grasp an unknown object stably. Thus, the developed 6-axis robot's finger force/moment sensor can be used for robot's gripper.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.300-305
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• 2009

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

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.2
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• pp.62-68
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• 1998

This paper presents the application of computer vision for the purpose of determining the position of the unknown object in the plane. The presented control method is to estimate the six view parameters representing the relationship between the image plane coordinates and the real physical coordinates. The estimation of six parameters is indispensable for transforming the 2-dimensional camera coordinates to the 3-dimensional spatial coordinates. Then, the position of unknown point is estimated based on the estimated parameters depending on the cameras. The suitability of this control scheme is demonstrated experimentally by determining position of the unknown object in the plane.