Fuzzy linear regression for contact identification

Author

Oussalah, M.

Author_Institution

Dept. of Mech. Eng., Katholieke Univ., Leuven, Heverlee, Belgium

Volume

4

fYear

2000

fDate

2000

Firstpage

3616

Abstract

In order to obtain an autonomous and intelligent system dealing with the uncertainties occuring in force controlled tasks, the determination of the parameters pertaining to the contact situation between the robot end-effector and the object is required. The paper describes a methodology based on fuzzy linear regression presenting two kinds of fuzzy linear models. The inputs are the force and velocity measurements. The results are compared with statistical regression. Moreover, the influence of initial data modelling in terms of extent as well the influence of the optimization constraint in the regression model are investigated

Keywords

force control; fuzzy set theory; manipulators; parameter estimation; possibility theory; statistical analysis; autonomous intelligent system; contact identification; force controlled tasks; fuzzy linear models; fuzzy linear regression; initial data modelling; optimization constraint; robot end-effector; Control systems; Force control; Force measurement; Intelligent robots; Intelligent systems; Linear regression; Mechanical engineering; Robot sensing systems; Shape; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1050-4729

Print_ISBN

0-7803-5886-4

Type

conf

DOI

10.1109/ROBOT.2000.845295

Filename

845295