Bi-criteria Velocity Minimization of Robot Manipulators Using a Linear Variational Inequalities-Based Primal-Dual Neural Network and PUMA560 Example
Authors: Zhang, Yunong1; Cai, Binghuang2; Zhang, Lei3; Li, Kene2
Source: Advanced Robotics, Volume 22, Numbers 13-14, 2008 , pp. 1479-1496(18)
Publisher: VSP, an imprint of Brill
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Abstract:
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., a primal-dual neural network based on linear variational inequalities (LVI)). Such a kinematic control scheme of redundant manipulators can incorporate joint physical limits such as joint limits and joint velocity limits simultaneously. Moreover, the presented kinematic control scheme can be formulated as a quadratic programming (QP) problem. As a real-time QP solver, the LVI-based primal-dual neural network is established with a simple piecewise linear structure and higher computational efficiency. Computer simulations performed based on a PUMA560 manipulator are presented to illustrate the validity and advantages of such a bi-criteria neural control scheme for redundant robots.Keywords: BI-CRITERIA VELOCITY MINIMIZATION; QUADRATIC PROGRAMMING; LINEAR VARIATIONAL INEQUALITIES-BASED PRIMAL-DUAL; PUMA560 ROBOT MANIPULATOR
Document Type: Research article
DOI: 10.1163/156855308X360578
Affiliations: 1: Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510275, China;, Email: ynzhang@ieee.org 2: Department of Electronics and Communication Engineering, Sun Yat-Sen University, Guangzhou 510275, China 3: School of Software, Sun Yat-Sen University, Guangzhou 510275, China
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