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Symbolic Analysis of Robot Base Parameter Set Using Grobner-Basis
Author(s) -
Harushisa Kawasaki,
Toshimi Shimizu
Publication year - 1998
Publication title -
journal of robotics and mechatronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.257
H-Index - 19
eISSN - 1883-8049
pISSN - 0915-3942
DOI - 10.20965/jrm.1998.p0475
Subject(s) - gröbner basis , kinematics , basis (linear algebra) , base (topology) , robot , matrix (chemical analysis) , mathematics , independence (probability theory) , polynomial , symbolic computation , set (abstract data type) , gaussian elimination , ideal (ethics) , symbolic data analysis , computer science , algorithm , artificial intelligence , mathematical analysis , theoretical computer science , geometry , gaussian , programming language , philosophy , statistics , physics , materials science , epistemology , classical mechanics , quantum mechanics , composite material
We analyzed base parameters for closed-loop robots using robot symbolic analysis based on the completion procedure in polynomial ideal theory. The robot dynamics regressor is represented as a matrix of multivariate polynomials and reduced to normal form based on Buchberger's algorithm by constructing reduced Grobner basis from kinematic constrained equations. The linear independence of the reduced regressor's column vectors is studied by Gauss-Jordan elimination. Original dynamic parameters are regrouped and some eliminated, depending on results. This omits the need to solve kinematic constrained equations explicitly, deriving all base parameters systematically in theory. An example is shown using robot symbolic analysis system: ROSAM 11.

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