• International Journal of Control, Automation, and Systems
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• 제4권1호
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• pp.17-29
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• 2006

A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.

• 한국축산시설환경학회지
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• 제13권3호
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• pp.179-186
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• 2007

The purpose of this study was kinematics analysis of the multi-joint robot manipulator for an automatic milking system. The multi-joint robot manipulator was consisted of one perpendicular link and four revolution links to attach simultaneously four teat cups to four teats of a milking cow. The local coordinates of each joints on the robot manipulator was given for kinematics analysis. The transformation of manipulator was able to be given by kinematics using Denavit-Hatenberg parameters. The value of inverse kinematics which was solved by two geometric solution methods. The kinematics solutions was verified by AutoCAD, MATLAB, simulation program was developed using Visual C++.

• Journal of Mechanical Science and Technology
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• 제20권7호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.953-958
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• 1992

This paper deals with the solution of inverse kinematics of the industrial FANUC robot with IBM PC386. The inverse kinematics of FANUC robot cannot be solved by the algebraical method, because arm matirix T$_{6}$ is very complex and 6-joint angles are associated with the position and the approach of end-effector. Instead we fuund otehr 5-joint angle by and algebraical method after finding .THETA.$_{1}$ value by a numerical method.d.

• 제어로봇시스템학회논문지
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• 제3권5호
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• pp.469-475
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• 1997

A method for solving the inverse kinematic problem of reclaimer is presented in this paper. The reclaimers in the raw yard are being used to dig raws and transfer them to the blast furnaces. The kinematic configuration of the reclaimer is different from that of commercially available robots, because it has a rotating disk with several buckets at the end of the boom to dig raws. The reclaimer has a redundancy due to the rotating disk : the degrees of freedom are greater than the number of forward kinematic equations. A plane equation in the 3-dimensional space is determined by using several points adjacent to the reclaiming point of the raw ores pile. A constraint is obtained from the relation ship of the plane equation and trajectories of the bucket of the reclaimer. Finally, a solution of the inverse kinematics of the reclaimer is determined by a numerical method.

• 로봇학회논문지
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• 제7권1호
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• pp.35-44
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• 2012

This paper presents a method to optimize motion planning for industrial manipulators with redundancy. For optimal motion planning, first of all, particular inverse kinematic solution is needed to improve efficiency for manipulators with redundancy working in various environments. In this paper, we propose three kinds of methods for solving inverse kinematics problems; numerical and combined approach. Also, we introduce methods for optimal motion planning using potential function considering the order of priority. For efficient movement in industrial settings, this paper presents methods to plan motions by considering colliding obstacles, joint limits, and interference between whole arms. To confirm improved performance of robot applying the proposed algorithms, we use two kinds of robots with redundancy. One is a single arm robot with 7DOF and another is a dual arm robot with 15DOF which consists of left arm, right arm with each 7DOF, and a torso part with 1DOF. The proposed algorithms are verified through several numerical examples as well as by real implementation in robot controllers.

• 대한기계학회논문집A
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• 제20권2호
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• pp.414-430
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• 1996

In this paper, a new kinematic structure of a parallel manipulator with six Cartesian degrees of freedom is proposed. It consists of a platform which is connected to a fixed base by means of 3-PPSP(parameters P, S denote the prismatic, spherical joints) subchains. Each subchain has a link which is concected to a passive prismatic joint at the one end and a passive spherical joint at the other. The spherical joint is then attached to perpendicularly arranged prismatic actuators which are fixed at the base. The spherical joint is then attached to perpendicularly arranged prismatic actuators which are fixed at the base. This arrangement provides a basis to control all six Cartesian degrees of motion of the platform in space. Due to its efficient architecture, the colsed-form solutions of the inverse and forward kinematics can be obtained. As a consequence, this new kinematic structure can be servo controlled using simple inverse kinematics becaese forward kinematics allows for measuring the platform's position and orientation in Cartesian space. Furthermore, the proposed structure provides an effective functional workspace. Series of simulations are performed to verify the results of the kinematics analyses.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.363-368
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• 1995

A general method of solving inverse kinematics of three-joint manipulator composed of revolute joints or prismatic joints or combinations of those joints is presented in this study. In completing real-time control, it is very important to obtain the closed form solutions of inverse kinematics rather than iterative numerical solutions, because iterative numerical solutions are generally much slower than the corresponding closed form solutions. If it is possible to obtain the inverse kinematic solutions for general cases of considering twist anlges and offsets, the manipulator work space can be designed and enlarged more effciently for specific task. Moreover, in idustrial manipulators, the effect of main three joints is larger than that of the other three joints related to orientation in the view of work space. Therfore the solutions of manin three-joint are considered. Even The inverse kinematic equations are complicatedly coupled, the systematical solving process by using symbolic calculation is presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.144-148
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• 1989

We solve the inverse kinematics problems in robotics by employing a neural network. In the practical situation. it is not easy to obtain the exact inverse kinematics solution, since there are many unforeseen errors such as the shift of a robot base the link's bending, et c. Hence difficulties follow in the trajectory planning. With the neural network, it is possible to train the robot motion so that the robot follows the desired trajectory without errors even under the situation where the unexpected errors are involved. In this work, Back-Propagation rule is used as a learning method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.65-68
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• 1995

This paper describes trajectory generation of a riobot arm by self-organizing neural networks. These neural networks are based on competitive learning without a teacher and this algorithm which is suitable for problems in which solutions as teaching signal cannot be defined-e.g. inverse dynamics analysis-is adopted to the trajectory generation problem of a robot arm. Utility of unsupervised learning algorithm is confirmed by applying the approximated solution of each joint calculated through learning to an actual robot arm in giving the experiment of tracking for reference trajectory.