DocumentCode :
2377442
Title :
Identification of robots dynamics with the Instrumental Variable method
Author :
Janot, A. ; Vandanjon, P.O. ; Gautier, M.
Author_Institution :
LIST, HAPTION S.A., Soulge sur Ouette, France
fYear :
2009
fDate :
12-17 May 2009
Firstpage :
1762
Lastpage :
1767
Abstract :
The identification of the dynamic parameters of robot is based on the use of the inverse dynamic model which is linear with respect to the parameters. This model is sampled while the robot is tracking ldquoexcitingrdquo trajectories, in order to get an over determined linear system. The linear least squares solution of this system calculates the estimated parameters. The efficiency of this method has been proved through the experimental identification of a lot of prototypes and industrial robots. However, this method needs joint torque and position measurements and the estimation of the joint velocities and accelerations through the pass band filtering of the joint position at high sample rate. So, the observation matrix is noisy. Moreover identification process takes place when the robot is controlled by feedback. These violations of assumption imply that the LS solution is biased. The Simple Refined Instrumental Variable (SRIV) approach deals with this problem of noisy observation matrix and can be statistically optimal. This paper focuses on this technique which will be applied to a 2 degrees of freedom (DOF) prototype developed by the IRCCyN Robotic team.
Keywords :
band-pass filters; feedback; least squares approximations; linear systems; matrix algebra; mobile robots; parameter estimation; position control; robot dynamics; statistical analysis; tracking filters; 2 DOF prototype; IRCCyN robotic team; feedback; inverse robots dynamics parameter identification; joint torque-position measurement; joint velocity-acceleration estimation; linear least square solution; observation matrix; over determined linear system; pass band filtering; simple refined instrumental variable method; statistical analysis; Electrical equipment industry; Instruments; Inverse problems; Least squares approximation; Linear systems; Parameter estimation; Position measurement; Prototypes; Service robots; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Conference_Location :
Kobe
ISSN :
1050-4729
Print_ISBN :
978-1-4244-2788-8
Electronic_ISBN :
1050-4729
Type :
conf
DOI :
10.1109/ROBOT.2009.5152228
Filename :
5152228
Link To Document :
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