Paper Info
Title
Minimal resolution needed for an accurate parametric identification - application to an industrial robot arm
Abstract
Parametric identification consists in estimating the values of physical parameters of robotic systems. The most popular methods consist in using the least squares regression because of their simplicity. However, we don't know how much they are dependent on the measurement accuracy and so on we ignore the necessary resolution they require to produce good quality results. This paper focuses on this issue and introduces a derivation of the CESTAC method, which will be applied to an industrial 6 degrees of freedom (DOF) serial robot, to estimate the minimal resolution indispensable for an accurate parametric identification.
Year
DOI
Venue
2007
10.1109/IROS.2007.4399476
San Diego, CA
Keywords
Field
DocType
industrial manipulators,least squares approximations,parameter estimation,regression analysis,CESTAC method,industrial 6 DOF serial robot,industrial robot arm,least squares regression,parametric identification,robotic systems
Least squares,Computer science,Regression analysis,Degrees of freedom (mechanics),Control engineering,Parametric identification,Industrial robot,Accuracy and precision,Estimation theory,Robot
Conference
ISBN
Citations 
PageRank 
978-1-4244-0912-9
0
0.34
References 
Authors
8
4
Name
Order
Citations
PageRank
Nicolas Marcassus100.34
P. O. Vandanjon2263.23
Alexandre Janot38612.37
Maxime Gautier447776.28