• 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.

• Journal of Sensor Science and Technology
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• v.21 no.3
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• pp.192-197
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• 2012

This paper describes the control of the hand fixing system attached to the finger rehabilitation robot for the rehabilitation exercise of patient's fingers. The finger rehabilitation robot is used to exercise the finger rehabilitation, and a patient's hand is safely fixed using the hand fixing system. In this paper, the hand fixing system was controlled with PD gains to fix a palm of the hand, and the characteristic test for the hand fixing system was carried out to sense the fixed hand movement of the front and the rear, that of the left and the right, and that of the upper. It is thought that the hand fixing system could safely fix the hand, and the movement of the fixed hand could be perceived using the five-axis force/moment sensor attached to the hand fixing system.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.94-103
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• 2019

The optimal grasping point of the object varies depending on the shape of the object, such as the weight, the material, the grasping contact with the robot hand, and the grasping force. In order to derive the optimal grasping points for each object by a three fingered robot hand, optimal point and posture have been derived based on the geometry of the object and the hand using the artificial neural network. The optimal grasping cost function has been derived by constructing the cost function based on the probability density function of the normal distribution. Considering the characteristics of the object and the robot hand, the optimum height and width have been set to grasp the object by the robot hand. The resultant force between the contact area of the robot finger and the object has been estimated from the grasping force of the robot finger and the gravitational force of the object. In addition to these, the geometrical and gravitational center points of the object have been considered in obtaining the optimum grasping position of the robot finger and the object using the artificial neural network. To show the effectiveness of the proposed algorithm, the friction cone for the stable grasping operation has been modeled through the grasping experiments.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.172-179
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• 2002

In a robot/vision system, the vision sensor, typically a CCD array sensor, is mounted on the robot hand. The problem of determining the relationship between the camera frame and the robot hand frame is refered to as the hand-eye calibration. In the literature, various methods have been suggested to calibrate camera and for sensor registration. Recently, one-step approach which combines camera calibration and sensor registration is suggested by Horaud & Dornaika. In this approach, camera extrinsic parameters are not need to be determined at all configurations of robot. In this paper, by modifying the camera model and including the lens distortion effect in the perspective transformation matrix, a new one-step approach is proposed in the hand-eye calibration.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.594-599
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• 2006

In this paper an anthropomorphic robot hand called SKKU Hand IIl is presented, which has a miniaturized fingertip tactile sensor. The thumb is designed as one part of the palm and multiplies the mobility of the palm. The fingertip tactile sensor, based on polyvinylidene fluoride (PVDF) and pressure variable resistor ink, is physically flexible enough to be deformed into any three-dimensional geometry. In order to detect incipient slip, a PVDF strip is arranged along the direction normal to the surface of the finger of the robot hand. Also, a thin flexible sensor to sense the static force as well as the contact location is fabricated into an arrayed type using pressure variable resistor ink. The driving circuits and the tactile sensing systems for the SKKU Hand II are embedded in the hand. Each driving circuit communicates with others using CAN protocol. SKKU Hand II is manufactured and its feasibility is validated through preliminary experiments.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.102-109
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• 2010

In this study, an anthropomorphic robot Hand, called "SKKU Hand III" is presented. The hand has thirteen DOF(Degree-Of-Freedom) and is designed based on the skeletal structure of the human hand. Each finger module(except thumb module) has three DOF and four joints with a saddle joint mechanism which has two DOF at the base joint. Two distal joints of the finger module are mechanically coupled by a timing belt and pulleys. The thumb module is composed of a finger module and an additional actuator, which makes it possible to realize the opposition between the thumb and the other fingers. In addition, the palm DOF of the human hand is mimicked with a spatial link mechanism between the index finger and the thumb. Thus, it can grasp objects more stably and more strongly. For the modularization of the robotic hand all the driving circuits are embedded in the hand, and only the communication lines supporting CAN protocol with DC power cable are given as an interface. Therefore, it is possible to apply it to any robot system the interface. To validate the feasibility of the SKKU Hand III, a series of the representative grasp experiments such as power, precision, intermediate grasp etc. are carried out with the object around us and its operation is demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.964-969
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• 2012

Robot hands capable of grasping or handling various objects are important for service robots to effectively aid humans. In particular, controlling a contact force and providing a compliant motion are essential when the hand is in contact with objects. Many dexterous robot hands equipped with force/torque sensors have been developed to perform force control, but they suffer from the complexity of control and high cost. In this paper, a low-cost robot hand based on SEA (Series Elastic Actuator), which is composed of compression spring, stretch sensor, and wire, is proposed. The grasping force can be estimated by measuring the compression length of spring, which would allow the hand to perform force control. A series of experimentations are carried out to verify the performance of force control of the proposed robot hand, and it is shown that it can successfully control the contact force without any additional force/torque sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.126.3-126
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• 2001

A new method to govern the navigation of a mobile robot is proposed based on the following two procedures: one is to achieve vision information by using a 2 D-O-F camera as a communicating medium between a man and a mobile robot and the other is to analyze and to behave according to the recognized hand gesture commands. In the previous researches, mobile robots are passively to move through landmarks, beacons, etc. To incorporate various changes of situation, a new control system manages the dynamical navigation of a mobile robot. Moreover, without any generally used expensive equipments or complex algorithms for hand gesture recognition, a reliable hand gesture recognition system is efficiently implemented to convey the human commands to the mobile robot with a few constraints.

• The Journal of Korea Robotics Society
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• v.10 no.4
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• pp.223-229
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• 2015

This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.