General redundancy optimization method for cooperating manipulators using quadratic inequality constraints

Authors
Citation
W. Kwon et Bh. Lee, General redundancy optimization method for cooperating manipulators using quadratic inequality constraints, IEEE SYST A, 29(1), 1999, pp. 41-51
Citations number
18
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
ISSN journal
10834427 → ACNP
Volume
29
Issue
1
Year of publication
1999
Pages
41 - 51
Database
ISI
SICI code
1083-4427(199901)29:1<41:GROMFC>2.0.ZU;2-W
Abstract
In redundancy optimization problems related to cooperating manipulators suc h as optimal force distribution, constraints on the physical limits of the manipulators should be considered. The constraints have been imposed mostly in the form of linear inequality constraints, which lead to polyhedric fea sible regions. In this paper, we propose quadratic inequality constraints ( QIC's), which lead to ellipsoidal feasible regions, to solve the optimizati on problem more efficiently, We investigate the effect of the use of QIC's from the points of view of problem size and change of the feasible region. To efficiently deal with the QIC's, we also propose the dual quadratically constrained quadratic programming (QCQP) method. In this method, the size o f the optimization problem is reduced so that the computational burden is l ightened, The proposed method and another well-known quadratic programming method are applied to the two PUMA robots system and compared with each oth er. The results show that the use of QIC's with the dual QCQP method allows for faster computation than the existing method.