Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5002540 | IFAC-PapersOnLine | 2016 | 6 Pages |
Abstract
The Prediction Error Method, developed in the field of system identification, handles the identification of discrete time noise model for systems linear with respect to the states and the parameters. However, robots are represented by continuous time models, which are not linear with respect to the states. In this article, we consider the issue of robot identification, taking into account the physical parameters as well as the noise model in order to improve the accuracy of the estimates. Thus, we developed a new technique to tackle this problem. The experimental results tend to show a real improvement in the estimation accuracy.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Mathieu Brunot, Alexandre Janot, Francisco Carrillo, Maxime Gautier,