DocumentCode
1860871
Title
Redundancy resolution for robot manipulators-comparison of computational efficiency between the SVDs, the fast similarity factorization and recursive formulation
Author
Koganezawa, Koichi
Author_Institution
Dep. of Mech. Eng., Tokai Univ., Kanagawa, Japan
fYear
2001
fDate
2001
Firstpage
89
Lastpage
95
Abstract
This paper discusses the computational efficiency of some procedures for solving the inverse kinematics problem of serial-link manipulators with redundant DOF. Two procedures that the author has newly developed, are compared to the most widely used SVD methods. One is called the fast similarity factorization (FSF) method, in which the symmetric matrix JJT J is the Jacobian of the manipulator) is factorized to GDGT (G is the orthogonal matrix and D is the diagonal matrix). Another procedure, that the author also developed, is a recursive formulation, in which the joint-variable variations are obtained n (the number of DOF of the manipulator) times recursive calculations. Both methods are fast and robust. The computer simulation for a seven DOF anthropomorphic type manipulator reveals the proposed methods are several times faster than the conventional algorithms based on the SVD.
Keywords
computational complexity; redundant manipulators; singular value decomposition; 7-DOF anthropomorphic type manipulator; FSF method; Jacobian; SVD; computational efficiency; diagonal matrix; fast similarity factorization; inverse kinematics problem; orthogonal matrix; recursive formulation; redundancy resolution; redundant DOF; robot manipulators; serial-link manipulators; singular value decomposition; symmetric matrix; Anthropomorphism; Computational efficiency; Computer simulation; Jacobian matrices; Kinematics; Manipulators; Robots; Robustness; State feedback; Symmetric matrices;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Robotics and Automation, 2001. Proceedings 2001 IEEE International Symposium on
Print_ISBN
0-7803-7203-4
Type
conf
DOI
10.1109/CIRA.2001.1013178
Filename
1013178
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