Titre :
|
Application of time series and polynomial learning networks to robot trajectory error control
|
Auteurs :
|
R. Boudreau ;
S. Darenfed ;
E. Biden
|
Type de document :
|
article/chapitre/communication
|
Année de publication :
|
1996
|
Format :
|
p.73-79
|
Langues:
|
= Anglais
|
Catégories :
|
STIC
|
Mots-clés:
|
APPRENTISSAGE
;
RESEAU DE NEURONES
;
SERIE CHRONOLOGIQUE
;
MODELISATION
;
ROBOT
|
Résumé :
|
A compensatory control scheme based on measured errors at the end-effector is proposed using polynomial learning networks and time series modeling. Based on experimental data from an industrial manipulator programmed for straight-line motion, trajectory deviations are modeled using both techniques. The performances of the models are compared at different locations in the workspace. It is shown that the robot arm signature can be obtained and that models from both techniques can be used to forecast trajectory errors. A method to implement the proposed scheme is also given.
|
Source :
|
Robotics and computer integrated manufacturing, vol.12, n°1
|