• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.561-565
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• 2000

This paper deals with dynamic walking and inverse dynamic analysis of the IWR biped walking robot. The system has nine bodies of the multibody dynamics. and all of the .joints of them are made up of the revolute joints at first. The problem of redundant constraint in double support phase is solved by changing the type of the joints considering kinematic relation. To make sure of its dynamic walking, the movement of balancing weight is determined by which satisfies not only the condition of ZMP by applying the principle of D'Alembert but also the contact condition of the ground. The modeling of IWR and dynamic walking are realized using DADS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.295-300
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• 1990

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield, Tank's neural network. The states of neurons represent joint velocities, and the connection weights are determined from the current value of the Jacobian matirx. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint positon. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.917-928
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• 2006

In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve nonlinear control problems. One of these ANNs applications is that of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to analyse of inverse kinematics of PUMA 560 type robot. The neural network is designed to find exact kinematics of the robot. The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for designing exact inverse model of the robot. The Unimation PUMA 560 is a robot with six degrees of freedom and rotational joints. Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot. From the simulation results, the proposed neural network has superior performance for modelling complex robot's kinematics.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1421-1429
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• 1994

An algorithm is developed for solving the inverse kinematic problem of a 6-degree-of-freedom robot with a wrist offset for which the closed form inverse solutions are not obtainable, but knowledge of one joint variable allows closed form solutions of the remaining joint variables. The algorithm does not require Forward Kinematics nor Jacobian but uses the implicit kinematic relationships between joint variables and the given hand position. An iterative back substitution method is used to solve the inversion and the optimal conditions of the convergence are incoporated. An example is given to illustrate the concepts, the solution procedure and its convergency.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.823-829
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• 2012

An excitation table is commonly used for vibration and ride tests for parts or assemblies of automobiles, aircrafts, or other heavy systems. The authors have analyzed several kinematic properties of an excitation table that is under development for heavy transport vehicles. It consists of one table and 7 linear hydraulic actuators. The authors have performed mobility analysis, inverse kinematics, forward kinematics, and singularity analysis. Especially, we have proposed a fast forward kinematic solution considering the limited motion of the excitation table. On the assumption that the motion variables such as rotation angles and displacements are small, the forward kinematic problem is converted to the observer problem of a linear system. This provides a fast solution. Also we have verified that there are no singularity points in the working range by numerical analysis.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.25 no.6
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• pp.504-510
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• 2016

Robots are widely utilized in many fields, and various demands need customized robots. This study proposes an optimal design method based on swarm intelligence for selecting the kinematic parameter of a manipulator according to the task space trajectory desired by the user. The optimal design method is dealt with herein as an optimization problem. This study is based on swarm intelligence-based optimization algorithms (i.e., ant colony optimization (ACO) and particle swarm optimization algorithms) to determine the optimal kinematic parameters of the manipulator. The former is used to select the optimal kinematic parameter values, whereas the latter is utilized to solve the inverse kinematic problem when the ACO determines the parameter values. This study solves a design problem with the PUMA 560 when the desired task space trajectory is given and discusses its results in the simulation part to verify the performance of the proposed design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.339-352
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• 2001

The inverse kinematics problem of Stewart platform is straightforward, but no closed form solution of the forward kinematic problem has been presented. Since we need the real-time forward kinematic solution in MIMO control and the motion monitoring of the platform, it is important to acquire the 6 DOF displacements of the platform from measured lengths of six cylinders in small sampling period. Newton-Raphson method a simple algorithm and good convergence, but it takes too long calculation time. So we reduce 6 nonlinear kinematic equations to 3 polynomials using Nairs method and 3 polynomials to 2 polynomials. Then Newton-Raphson method is used to solve 3 polynomials and 2 polynomials respectively. We investigate operation counts and performance of three methods which come from the equation reduction and Newton-Raphson method, and choose the best method.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.744-749
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• 2007

Kinematic and kinetic analysis has been performed for Soft Golf swings utilizing realistic three dimensional computer simulations based on three dimensional motion tracking data. Soft Golf is a newly developed recreational sport in South Korea aimed to become a safe and easy-to-learn sport for all ages. The advantage of Soft Golf stems from lighter weight of the club and much larger area of the sweet spot. This paper tries to look into kinematic and kinetic aspects of soft golf swings compared to regular golf swing and find the advantages of lighter Soft Golf clubs. For this purpose, swing motions of older aged participants were captured and kinematic analysis was performed for various kinematic parameters such as club head velocity, joint angular velocity, and joint range of motions as a pilot study. Kinetic analysis was performed by applying kinematic data to computer simulation models constructed from anthropometric database and the measurements from the participants. The simulations were solved using multi-body dynamics solver. Firstly, the kinematic parameters such as joint angles were obtained by solving inverse dynamics problem based on motion tracking data. Secondly, the kinetic parameters such as joint torques were obtained by solving control dynamics problem of making joint torque to follow pre-defined joint angle data. The results showed that mechanical loadings to major joints were reduced with lighter Soft Golf club.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.3
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• pp.5-12
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• 2008

This paper presents the features of an impact angle constrained open-loop optimal trajectory which is given by a function of initial conditions and optimal guidance gains. Using missile motion described by linearized kinematic equations and a proper form of performance index, an inverse optimal problem is suggested to investigate the gains related to the performance index. The flight trajectory and time-to-go can be shaped in terms of the optimal guidance gains. The results are evaluated by 3-DOF simulation.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.211-218
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• 1999

The traditional robot manipulators are actuated by continuous range of motion actuators such as motors or hydraulic cylinders. However, there are many applications of mechanisms and robotic manipulators where only a finite number of locations need to be reached, and the robot’s trajectory is not important as long as it is bounded. Binary manipulator uses actuators which have only two stable states. As a result, binary manipulators have a finite number of states. The number of states of a binary manipulator grows exponentially with the number of actuators. This kind of robot manipulator has some advantage compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. And this kind of robot manipulator has a fault tolerant mechanism because of kinematic redundancy. In this paper, we solve the inverse kinematic problem of a binary parallel robot manipulator using neural network and test the validity of this structure using some arbitrary points m the workspace of the robot manipulator. As a result, we can show that the neural network can find the nearest feasible points and corresponding binary states of the joints of the robot manipulator