ICRA 2011 Paper Abstract

Close

Paper TuA211.3

Hamon, Pauline (CEA, LIST), Gautier, Maxime (Université de Nantes), Garrec, Philippe (CEA)

New Dry Friction Model with Load and Velocity-Dependency and Dynamic Identification of Multi-DOF Robots

Scheduled for presentation during the Regular Sessions "Direct/Inverse Dynamics Formulation" (TuA211), Tuesday, May 10, 2011, 10:35−10:50, Room 5F

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on March 30, 2020

Keywords Direct/Inverse Dynamics Formulation, Calibration and Identification

Abstract

Usually, the joint transmission friction model for robots is composed of a viscous friction force and of a constant dry sliding friction force. However, according to the Coulomb law, the dry friction force depends linearly on the load driven by the transmission, which has to be taken into account for robots working with large variation of the payload or inertial and gravity forces. Moreover, for robots actuating at low velocity, the Stribeck effect is visible and has to be included in the model. This paper proposes a new inverse dynamic identification model for n degrees of freedom (dof) serial robot, where the dry sliding friction force is a linear function of both the dynamic and the external forces, with a velocity-dependent coefficient. A new identification procedure is carried out. At a first step, the friction model parameters are identified for each joint (1dof) , moving one joint at a time. At a second step, these values are fixed in the n dof dynamic model for the identification of all robot inertial and gravity parameters. For the two steps, the identification groups all the joint data collected while the robot is tracking planned trajectories with different payloads to get a global least squares estimation of inertial and new friction parameters. An experimental validation is carried out with an industrial 3 dof robot.

 

 

Technical Content © IEEE Robotics & Automation Society

This site is protected by copyright and trademark laws under US and International law.
All rights reserved. © 2002-2020 PaperCept, Inc.
Page generated 2020-03-30  01:15:09 PST  Terms of use