ICRA'09 Paper Abstract

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Paper FrA7.3

Janot, Alexandre (Haption SA), Vandanjon, Pierre Olivier (Laboratoire Central des Pont et Chaussées), Gautier, Maxime (Université de Nantes)

Identification of Robots Dynamics with the Instrumental Variable Method

Scheduled for presentation during the Regular Sessions "Dynamics" (FrA7), Friday, May 15, 2009, 09:10−09:30, Room: 405

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 21, 2022

Keywords Calibration and Identification, Industrial Robots

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 “exciting” 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.

 

 

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