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Bi-criteria velocity minimization of robot manipulators using LVI-based primal-dual neural network and illustrated via PUMA560 robot arm

Published online by Cambridge University Press:  05 June 2009

Yunong Zhang  and
Kene Li
Yunong Zhang*
Affiliation:
Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510275, China
Kene Li
Affiliation:
Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510275, China
*
*Corresponding author. E-mail: ynzhang@ieee.org
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Summary

In this paper, to diminish discontinuity points arising in the infinity-norm velocity minimization scheme, a bi-criteria velocity minimization scheme is presented based on a new neural network solver, i.e., an LVI-based primal-dual neural network. Such a kinematic planning scheme of redundant manipulators can incorporate joint physical limits, such as, joint limits and joint velocity limits simultaneously. Moreover, the presented kinematic planning scheme can be reformulated as a quadratic programming (QP) problem. As a real-time QP solver, the LVI-based primal-dual neural network is developed with a simple piecewise linear structure and high computational efficiency. Computer simulations performed based on a PUMA560 manipulator model are presented to illustrate the validity and advantages of such a bi-criteria velocity minimization neural planning scheme for redundant robot arms.

Keywords

Redundant manipulatorsMinimum infinity-norm schemeBi-criteria inverse kinematicsQuadratic programmingNeural networks
Type
Article
Information
Robotica , Volume 28 , Issue 4 , July 2010 , pp. 525 - 537
Copyright
Copyright © Cambridge University Press 2009

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