Title :
Fuzzy linear regression for contact identification
Author_Institution :
Dept. of Mech. Eng., Katholieke Univ., Leuven, Heverlee, Belgium
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;
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-5886-4
DOI :
10.1109/ROBOT.2000.845295
