• 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 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.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.100-104
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• 2008

In this paper, intelligent filtering methodology for masterarm translation signal is proposed. Fidelity and stability are contradicting factors in teleoperation. Human hand trembling filtering is one of the problems in telemanipulation field. During every operation the hand has a certain vibration that can affect the quality of teleoperation, especially in carrying FPD (Flat Panel for Display), nanomanipuation and other precise tasks. It is very important to study the kinesthetic perception of the human and to optimize the teleoperation system accordingly. To cancel out the influence of human's hand vibration the signal from the masterarm should be filtered. One of the feasible solutions is to use an intelligent filter based on fuzzy logic, which is a very flexible instrument. Applying intelligent filtering methodology, we can use some heuristic methods to solve the filtering problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.135-138
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• 2007

In this paper, intelligent filtering methodology for masterarm translation signal is proposed. Fidelity and stability are contradicting factors in teleoperation. Human hand trembling filtering is one of the problems in telemanipulation field. During every operation the hand has a certain vibration that can affect the quality of teleoperation, especially in carrying FPD (Flat Panel for Display), nanomanipuation and other precise tasks. It is very important to study the kinesthetic perception of the human and to optimize the teleoperation system accordingly. To cancel out the influence of human's hand vibration the signal from the masterarm should be filtered. One of the feasible solutions is to use an intelligent filter, which is a very flexible instrument. Applying intelligent filtering methodology, we can use some heuristic methods to solve the filtering problem.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1093-1098
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• 2003

In this paper, a practical methodology of hand-manipulator motion coordination for indoor service robot is introduced. This paper describes the procedures of opening door performed by service robot as a noticeable example of motion coordination. This paper presents well-structured framework for hand-manipulator motion coordination, which includes intelligent sensor data interpretation, object shape estimation, optimal grasping, on-line motion planning and behavior-based task execution. This proposed approach is focused on how to integrate the respective functions in harmony and enable the robot to complete its operation under the limitation of usable resources. As a practical example of implementation, the successful experimental results in opening door whose geometric parameters are unknown beforehand are provided.

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.205-212
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• 2009

This paper proposes a biomimetic hand prosthesis with tendon-driven five fingers. Each finger is composed of a distal-middle phalange, a proximal phalange and a metacarpal bone, which are connected to a link mechanism. The finger flexion is a resultant motion by pulling a wire to serve as a tendon, but the finger extension is performed by an elastic mechanism composed of a restoration spring. The designed hand prosthesis with tendon-driven five fingers has totally six degrees of freedom. But its weight is merely 400.73g. The hand can perform various hand functions such as the grasping and the hand postures. From experimental results, we show that the proposed hand prosthesis is useful to amputees as a prosthetic hand.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.396-402
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• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.50-53
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• 2003

We describe a method for estimating new hand views from a single 2D hand image using decomposed approach with subgroup-based scheme. With this method, we can get the simplicity in the sense of computation by comparing the image with models in the promising subgroup instead of comparing with all models. It shows more effectiveness in recognition by process depend on each subgroup and easy of extension.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.