• 대한수학교육학회지:학교수학
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• 제11권2호
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• pp.281-299
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• 2009

본 논문에서는 동적조작 환경 속에서 이루어지는 물리적 실험을 도구로 선택하여 발명되고 있는 과정으로서의 수학을 학생들이 접할 수 있도록 1) 정의 도입 방식을 변화시켜 의미 있는 수학적 정의를 만들어내는 2) 시각화를 통한 연속성 사고 능력을 강화하는 3) 발견과 탐구를 통하여 수학을 만들어내는 4) 문제를 제기하고 일반화하는 능력을 강화하는 사례들을 제시하고 분석함으로써 수학교과과정에 어떻게 동적조작 환경을 융합시킬 수 있는가를 보였다. 이러한 교수-학습 환경 하에서 발생할 수 있는 문제점을 분석하고, 이러한 문제점을 해결하기 위한 교사의 역할에 대해 논하였다.

• The Journal of Korean Physical Therapy
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• 제29권2호
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• pp.95-100
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• 2017

Purpose: This study aimed to evaluate the changes in dorsiflexion and balance following proximal and distal tibiofibular joint manipulation in individuals with a history of lateral ankle sprain (LAS). Methods: Fifteen participants with a history of unilateral LAS, exhibiting a restriction in ankle dorsiflexion were included in this study. LAS ankle received a manipulation to the proximal and distal tibiofibular joint, while the opposite control ankle received no manipulation intervention. The outcome measures included ankle dorsiflexion and balance. Ankle dorsiflexion was measured using weight-bearing lunge test. Static and dynamic balances were measured using the overall, anterioposterior, and mediolateral balance index via the biodex balance system. Measurements were obtained prior to and following manipulation. Results: This study showed that ankle dorsiflexion and dynamic balance were improved following the manipulation compared to those prior to the manipulation (p<0.05). There was no significant change in static balance (p>0.05). Conclusion: The joint manipulation technique applied to the ankle of those with a history of LAS appears to improve ankle dorsiflexion and dynamic balance. This suggest that a manipulation to the proximal and distal tibiofibular joint could be provided as preliminary data regarding the prophylactic effects of recurrent LAS.

• 제어로봇시스템학회논문지
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• 제12권11호
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• pp.1111-1118
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• 2006

This paper covers topics related to the investigations for the problem of sensorless vibratory orienting of polygonal parts with high probability through dynamic simulation. The author's program for mechanical systems with changing topologies was experimentally validated and was used as a simulation and design tool for motion behaviors of the vibratory parts-orienting system in the dynamic environment. A flat level vibrating bar is proposed as a means of orienting parts. Dynamic manipulation, in which a part is repeatedly caught and tossed by the bar without sensing, forms the fundamental manipulation strategy. This paper presents how to plan vibratory manipulation strategies that can orient a small rigid polygonal part using interaction between the part and the vibrating bar without requiring sensing. The planned motion strategies have been experimentally validated to show how the dynamic simulation can be used to find favorable vibration parameters for a given part without knowledge of their initial orientations.

• 로봇학회논문지
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• 제8권1호
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• 한국지능시스템학회논문지
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• 제20권6호
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• pp.774-779
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• 2010

본 논문에서는 다양한 서비스를 제공할 수 있는 모바일 매니퓰레이션 시스템에 장착된 로봇 팔과 몸체 메커니즘의 동적 운동 특성을 분석하고자 한다. 이 목적을 위하여 팔 및 몸체 메커니즘의 동특성 요소를 제시하고, 경로 추종 시뮬레이션을 통하여 이러한 요소들의 주요 동향을 확인한다. 또한, 이러한 요소들이 몸통, 어깨 및 팔꿈치 운동에 미치는 영향을 고찰한다. 이러한 분석은 로봇 팔과 몸체 메커니즘을 갖는 모바일 매니퓰레이션 시스템의 효과적인 조작행위를 위하여 유용하게 활용될 수 있을 것으로 기대한다.

• 한국실내디자인학회:학술대회논문집
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• 한국실내디자인학회 2004년도 추계학술발표대회 논문집
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• pp.92-97
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• 2004

This purpose of this study was about the analysis on the dynamic expression of geometric manipulation in interior composition elements. The paradigm of contemporary times became different from paradigm of modern times. The change of paradigm is caused by the side effect of paradigm of pre-times. In the contemporary architectural condition, architecture have a tendency to plural characteristics. This study investigates systemically ‘the DYNAMISM’ as a part of contemporary interior space's feature, based on geometric manipulation in interior composition elements. First of all, the dynamic characteristics of architectural space. The second, relationship between the architecture and geometric manipulation.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.228-237
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• 2004

This paper provides a motion analysis of soft-fingertip object manipulation tasks by presenting a dynamic model of multi-fingered object manipulations with soft fingertips. It is fundamentally observed that soft fingertips employed in a multi-fingered hand generate some deformation effects during the manipulation process and also that those effects are closely related to the behavior of the manipulated object. In order to analyze the motion of using soft fingertips, a dynamic manipulation control scheme is presented. Simulation and experimental results demonstrate the motion of soft-fingertips applied in object manipulating tasks and are further used to discuss the characteristics of soft-fingertip motions.

• Journal of Advanced Research in Ocean Engineering
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• 제3권3호
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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.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제16권2호
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• pp.107-123
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• 2012

A group of twenty-nine high school student-teachers were given a set of mathematical propositions focusing on shape-to-shape transformations. Their task was to determine through hands-on manipulation and use of dynamic software that each shape be transformed into an area equivalent rectangular region. This paper reports on a classroom-based research.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.124-129
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• 1992

The goal of the proposed Intelligent Assisting System - IAS is to assist human operators in an intelligent way, while leaving decision and goal planning instances for the human. To realize the IAS the very important issue of manipulation skill identification and analysis has to be solved, which then is stored in a Skill Data Base. Using this data base the IAS is able to perform complex manipulations on the motion control level and to assist the human operator flexibly. We propose a model for manipulation skill based on the dynamics of the grip transformation matrix, which describes the dynamic transformation between object space and finger joint space. Interaction with a virtual world simulator allows the calculation and feedback of appropriate forces through controlled actuators of the sensor glove with 10 degrees-of-freedom. To solve the sensor glove calibration problem, we learn the nonlinear calibration mapping by an artificial neural network(ANN). In this paper we also describe the experimental system setup of the skill acquisition and transfer system as a first approach to the IAS. Some simple manipulation examples and simulation results show the feasibility of the proposed manipulation skill model.