• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.320-327
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• 2005

A new mechanism for hyper redundant manipulator (HRM) is presented, which comprises of serially assembled compound three-bar linkages (CTL). The CTL mechanism has some unique properties. This paper presents the forward and inverse kinematics of this mechanism and shows the simulation of the HRM havig 9 CTL units. The recursive algorithm of the inverse kinematics that the author originally developed is employed. It is fast and stable ; moreover, it enables us to obtain a solution in which the end-point of the HRM is controlled by a portion of joints. It also presents the method of the dynamical analysis. There exist kinematical constraints in the proposed closed linkage mechanism. In the dynamic analysis constraints are sufficiently sustained by the constraint stabilization method that the author developed. The mechanical structure of the HRM having some CTL units that is under construction is shown.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.224-228
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• 2000

In this paper, the kinematics of the new type of parallel manipulator is studied, and neural network is applied to solve the forward kinematics problem. The parallel manipulator, called a Stewart platform, has an easy and unique solution about the inverse kinematics, however the forward kinematics is difficult to get the solution because of the lack of an efficient algorithm due to its highly nonlinearity. This paper proposes the neural network scheme as an alternative Newton-Raphson method. The neural network is found to improve its accuracy by adjusting the offset of the result obtained.

• 한국정밀공학회지
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• 제32권3호
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• pp.253-261
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• 2015

A parallel mechanism with redundancy can be regarded as a means for not only maximizing the benefits of parallel mechanisms but also overcoming their drawbacks. We proposed a novel parallel mechanism by eliminating an unnecessary degree of freedom of the configuration space. Because of redundancy, however, the solution for the inverse kinematics of the developed parallel mechanism is infinite. Therefore, we defined a cost function that can minimize the movement time to the target orientation and found the solution for the inverse kinematics by using a numerical method. In addition, we proposed a method for determining the boundary of the geometric singularity in order to avoid singularities.

• 대한전자공학회논문지SP
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• 제47권6호
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• pp.39-47
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• 2010

영상 기반의 모션 캡처에 대한 연구는 인체의 특징 영역 검출, 정확한 자세 추정 및 실시간 성능 등의 문제를 풀기 위해 많은 연구가 진행되고 있다. 특히, 인체의 많은 관절 정보를 복원하기 위해 다양한 방법이 제안되고 있다. 본 논문에서는 수치적인 역운동학 방법의 단점을 개선한 실시간 모션 캡처 방법을 제안한다. 기존의 수치적인 역운동학 방법은 많은 반복 연산이 필요하며, 국부최소치 문제가 발생할 수 있다. 본 논문에서는 이러한 문제를 해결하기 위해 기존의 수치적인 역운동학 해법과 UKF를 결합하여 중간관절을 복원하는 방법을 제안한다. 수치적인 역운동학의 해와 UKF를 결합함으로써, 중간 관절 추정 시 최적값에 보다 안정적이고 빠른 수렴이 가능하다. 모션 캡처를 위해 먼저, 배경 차분과 피부색 검출 방법을 이용하여 인체의 특징 영역을 추출한다. 다수의 카메라로부터 추출된 2차원 인체 영역 정보로부터 3차원 정보를 복원하고, UKF와 결합된 수치적인 역운동학 해법을 통해 동작자의 중간 관절 정보를 추정한다. 수치적인 역운동학의 해는 UKF의 상태 추정 시 안정적인 방향을 제시하고, UKF는 다수의 샘플을 기반으로 최적 상태를 찾음으로써, 전역해에 보다 빠르게 수렴한다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.580-583
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• 2002

This paper presents a novel pose description corresponding to the structure characteristics of parallel manipulators, which is convenient and intuitionistic to us. A class of 3-RSR parallel manipulator is considered here. Through analysis on geometry theory, we obtain a new method of the closed-form solution to the forward kinematics. The closed-form solution contains two different meanings-analytical and real-time. So we reach the goal of practical application and control. A numerical example is also presented and are verified by an inverse kinematics analysis. It shows that the method has a practical value for real-time control.

• 한국공작기계학회논문집
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• 제17권3호
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• pp.1-7
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• 2008

This paper describes the kinematics which is a new type of parallel manipulator, and the neural network is applied to solving the forward kinematics problem. The parallel manipulator called it as a Stewart platform has an easy and unique solution about the inverse kinematics. However, the forward kinematics is difficult to get a solution because of the lack of an efficient algorithm caused by its highly nonlinearity. This paper proposes the neural network scheme of an Newton-Raphson method alternatively. It is found that the neural network can be improved its accuracy by adjusting the offset of the obtained result.

• 한국자동차공학회논문집
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• 제9권1호
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• pp.156-162
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• 2001

An effective and practical method is presented for solving the forward kinematics of a 6-DOF Stewart Platform, using neural network algorithm together with Newton-Raphson method. An approximated solution is obtained from trained neural network, then it is used as an initial estimate for Newton-Raphson method. A series of accurate solutions are calculated with reasonable speed for the entire workspace of the platform. The solution procedure can be used for driving a real-time simulation platform.

• 한국정밀공학회지
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• 제23권7호
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• pp.76-83
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• 2006

In this paper, an analysis on a new robot manipulator developed for the side buffing of the shoes is presented. The robot manipulator is composed of five degrees of freedom. An analysis on the forward and inverse kinematics was performed. Through the analysis, an analytic solution was derived for the joint angles corresponding to the position and orientation of the tool in the Cartesian coordinates. The hardware system of the robot composed of the control system, input/output interface system, and related electronic system was developed. The communication system was also developed to interact the robot with the related surrounding systems. A graphic user interface(GUI) program including the forward/inverse kinematics, control algorithm, and communication program was developed using visual C++ language.

• 대한전기학회논문지
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• 제39권9호
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• pp.985-996
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• 1990

An inverse kinematic solution of a robot manipulator using multilayer perceptrons is proposed. Neural networks allow the solution of some complex nonlinear equations such as the inverse kinematics of a robot manipulator without the need for its model. However, the back-propagation (BP) learning rule for multilayer perceptrons has the major limitation of being too slow in learning to be practical. In this paper, a new algorithm named Dynamically Reconfiguring BP is proposed to improve its learning speed. It uses a modified version of Kohonen's Self-Organizing Feature Map (SOFM) to partition the input space and for each input point, select a subset of the hidden processing elements or neurons. A subset of the original network results from these selected neuron which learns the desired mapping for this small input region. It is this selective property that accelerates convergence as well as enhances resolution. This network was used to learn the parity function and further, to solve the inverse kinematic problem of a robot manipulator. The results demonstrate faster learning than the BP network.

• 한국생산제조학회지
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• 제22권2호
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• pp.256-262
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• 2013

This paper presents a linear path control algorithm for NeuroMate robot in a skull drilling system. For the path control inverse kinematics of the robot is analyzed and a linear interpolation algorithm is presented. A geometric approach is used for solving inverse kinematic equations for the robot. Four feasible solutions are found through the approach. The approach gives geometric insights for selecting the best solution from the feasible solutions. The presented linear interpolation algorithm computes a next position considering current velocity and remaining distance to the target position. Presented algorithm is implemented and tested in a skull drilling system.