Authors:
Pierre-Olivier Vandanjon
1
;
Alexandre Janot
2
;
Maxime Gautier
3
and
Flavia Khatounian
2
Affiliations:
1
LCPC, France
;
2
CEA/LIST Interactive Robotic Unit, France
;
3
IRCCyN, Robotic team, France
Keyword(s):
Parameters identification, inverse model, least squares method, simple refined instrumental variable method.
Related
Ontology
Subjects/Areas/Topics:
Cybernetics
;
Health Engineering and Technology Applications
;
Human-Robots Interfaces
;
Informatics in Control, Automation and Robotics
;
NeuroSensing and Diagnosis
;
Neurotechnology, Electronics and Informatics
;
Robotics and Automation
Abstract:
Parametric identification requires a good know-how and an accurate analysis. The most popular methods consist in using simply the least squares techniques because of their simplicity. However, these techniques are not intrinsically robust. An alternative consists in helping them with an appropriate data treatment. Another choice consists in applying a robust identification method. This paper focuses on a comparison of two techniques: a “helped” least squares technique and a robust method called “the simple refined instrumental variable method”. These methods will be applied to a single degree of freedom haptic interface developed by the CEA Interactive Robotics Unit.