• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.237-242
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• 2023

Research on high-performance walking robots is being actively conducted, and quadruped walking robots are receiving a lot of attention due to their excellent mobility and adaptability on uneven terrain, but they are difficult to introduce and utilize due to high cost. In this paper, to increase utilization by applying intelligent functions to a low-cost quadruped robot, we present a method of improving uneven terrain overcoming ability by mounting IMU and reinforcement learning on embedded board and automatically detecting objects using camera and deep learning. The robot consists of the legs of a quadruped mammal, and each leg has three degrees of freedom. We train complex terrain in simulation environments with designed 3D model and apply it to real robot. Through the application of this research method, it was confirmed that there was no significant difference in walking ability between flat and non-flat terrain, and the behavior of performing person detection in real time under limited experimental conditions was confirmed.

• KSTLE International Journal
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• v.2 no.2
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• pp.93-102
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• 2001

Ball bearings have been widely used for the spindle motor bearing in various kinds of information storage devices. Recently many researchers have been trying to replace ball bearings with fluid film bearings because of their superior NRRO(non-repeatable runout) characteristics. In this study, a numerical analysis has been conducted for the complicate bearing system composed of herringbone groove journal bearing and spiral groove thrust bearing for the spindle motor of the information storage device. At first, spindle motor bearing is modeled as journal bearing part and thrust bearing part separately, and then observed various influences of geometric parameters. Previous studies had considered only the translational motion of the journal bearing. However, this study takes the additional 2-degree of freedom rotation into consideration to attempt to describe the real motion of the spindle bearing. As a result, rotational stiffness coefficients and rotational damping coefficients are obtained. In addition, a spindle bearing system made up of four bearings is modeled and interpreted at once and coefficients of dynamic characteristics of each bearing are obtained. Finally, an eigen analysis of bearing system is made with these results. Through this analysis, it is possible to estimate an unstable condition of the system for given geometric parameters and to propose a method which is able to avoid the unstable condition by a proper adjustment of geometric parameters.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.678-681
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• 2004

In this paper, efficient tracking of a moving object using optimal representative blocks is implemented by a mobile robot with a pan-tilt camera. The key idea comes from the fact that when the image size of moving object is shrunk in an image frame according to the distance between the camera of mobile robot and the moving object, the tracking performance of a moving object can be improved by changing the size of representative blocks according to the object image size. Motion estimation using Edge Detection(ED) and Block-Matching Algorithm(BMA) is often used in the case of moving object tracking by vision sensors. However these methods often miss the real-time vision data since these schemes suffer from the heavy computational load. In this paper, the optimal representative block that can reduce a lot of data to be computed, is defined and optimized by changing the size of representative block according to the size of object in the image frame to improve the tracking performance. The proposed algorithm is verified experimentally by using a two degree-of-freedom active camera mounted on a mobile robot.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.104-112
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation forthe identification of a face shape. The proposed algorithm uses face shape asinput information in a single camera environment and divides only face area through preprocessing process. However, it is not easy to accurately recognize the face area that is sensitive to lighting changes and has a large degree of freedom, and the error range is large. In this paper, we separated the background and face area using the brightness difference of the two images to increase the recognition rate. The brightness difference between the two images means the difference between the images taken under the bright light and the images taken under the dark light. After separating only the face region, the face shape is recognized by using the self-organization feature map (SOFM) algorithm. SOFM first selects the first top neuron through the learning process. Second, the highest neuron is renewed by competing again between the highest neuron and neighboring neurons through the competition process. Third, the final top neuron is selected by repeating the learning process and the competition process. In addition, the competition will go through a three-step learning process to ensure that the top neurons are updated well among neurons. By using these SOFM neural network algorithms, we intend to implement a stable and robust real-time face shape recognition system in face shape recognition.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.926-936
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• 2017

The nonlinear behavior and the high performance requirement are the main problems that appear in the design of manipulator robots and their controllers. For that reason, the simulation, real-time execution and comparison of the performance of controllers applied to a robot with three degrees of freedom are presented. Five controllers are prepared to test the robot's dynamic model: predictive; hyperbolic sine-cosine; sliding mode; hybrid composed of a predictive + hyperbolic sine-cosine controller; and adaptive controller. A redundant robot, a communication and signal conditioning interface, and a simulator are developed by means of the MatLab/Simulink software, which allows analyzing the dynamic performance of the robot and of the designed controllers. The manipulator robot is made to follow a test trajectory which, thanks to the proposed controllers, it can do. The results of the performance of this manipulator and of its controllers, for each of the three joints, are compared by means of RMS indices, considering joint errors according to the imposed trajectory and to the controller used.

• Advances in aircraft and spacecraft science
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• v.5 no.4
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• pp.477-498
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• 2018

The main goal of this article is to validate a methodological process in Actran MSC Software, that is based on the Finite Element Method, to evaluate the comfort in the cabin of a regional aircraft and to study the noise and vibrations reduction through the fuselage by the use of innovative materials. In the preliminary work phase, the CAD model of a fuselage section was created representing the typical features and dimensions of an airplane for regional flights. Subsequently, this model has been imported in Actran and the Sound Pressure Level (SPL) inside the cabin has been analyzed; moreover, the noise reduction through the fuselage has been evaluated. An important investigation and data collection has been carried out for the study of the aircraft cabin to make it as close as possible to a real problem, both in geometry and in materials. The mesh of the structure has been built from the CAD model and has been simplified in order to reduce the number of degrees of freedom. Finally, different fuselage configurations in terms of materials are compared: in particular, aluminum, composite and sandwich material with composite skins and poroelastic core are considered.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.160-163
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• 1993

In this paper, design of an automatic grinding robot system for car brazing bead is introduced. Car roof and side panels are joined using brazing, and then the brazing bead is processed so that the bead is invisible after painting. Up to now the grinding process is accomplished manually. The difficulties in automation of the grinding process are induced by variation of position and shape of the bead and non-uniformity of the grinding area due to surface deformation. For each car, the grinding area including the brazing bead is sensed and then modeled using a 2-D optical sensor system. Using these model data, the position and the direction of discrete points on the car, body surface are obtained to produce grinding path for a 6 degrees of freedom grinding robot. During the process, it is necessary to sense the reaction forces continuously to prepare for the unexpected circumstances. In addition, to meet the line cycle time it is necessary to reduce the required time in sensing, signal processing, modeling, path planning and data transfer by utilizing real-time communication of the information. The key technique in the communication and integration of the complex information is obtaining in-field reliability. This automatic grinding robot system may be regarded as a jump in the intelligent robot processing technique.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.

• Journal of the Korean Home Economics Association
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• v.35 no.6
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• pp.1-13
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• 1997

Hipp8ie style was introduced in 1960s when young generation's movement against industrial society and mass culture was spread. Its value was to go back to "Real and Pure Nature". Hippie originated from "Human Be-in" which was on-violent revolution held in sanfrancisco. American Hippie style was represented through freedom and love based on drug and psychedelic culture which were created by the young generation who were against traditional esthetic value as well as the moral and material value. However, Hippie style was represented differently in France. The privilege classes such as artists who were interested in surrealism, art negro and primitive culture, the intelligentsia like Montparnass in Paris, accepted Hippie style faster than ordinary people did. therefor, Hippie style in france was represented as an esthetic mode not a symbol of anti-culture and anti-policy. The general public imitated the style of the privileged classes and coordinated their style according to their personality without any standard such as blue jeans, ethnic, psychedelic, mini, mods, beatnik, etc. Yves Saint Laurent who was influenced by hippies led the mode of Paris to introduce "Africa", "Saharienne", "Pathwork". therefore, in 1960's fashion in Paris, everything was possible because of too many changes in fashion and refusal of accepting vogue.