A Petri Net Modelling of an Adaptive Learning Control Applied to an Electric Wheelchair - @rchiveSIC Accéder directement au contenu
Communication Dans Un Congrès Année : 2005

A Petri Net Modelling of an Adaptive Learning Control Applied to an Electric Wheelchair

Résumé

The aim of this paper is to present a Petri net based approach of a codesign methodology, in order to obtain optimized hardware/software solutions. An example of application is given for a neural control lever of a wheelchair. The research of solutions to the problem of hardware/software codesign, is a major task in the definition of a unique, structured and automatic methodology, providing the acceleration of design process and the dynamic evaluation of different compromises. data flow Petri nets are an efficient solution to make it possible and the use of a hardware description language, allows their implementation on programmable chips. The example described in this paper deals with a wheelchair whose commands can adapt to handicap. For some handicapped people, the use of a wheelchair can be difficult, due to weak physical capacities or cognitive troubles. So, the human-machine interface must be modular, configurable and easy to implement. It must bring reliability and use non specific material as often as possible. Therefore, the FRACAH project (Fauteuil Roulant A Commande Adaptee au Handicap) has been developed in order to proceed to evaluations. For example, its lever is handled by an artificial neural network that records functional limitations of the hand, and then compensates them. Some experiments have been done with hand disabled students.
Fichier non déposé

Dates et versions

sic_01798077 , version 1 (23-05-2018)

Identifiants

Citer

Alexandre Abellard, Mohamed Moncef Ben Khelifa, Moez Bouchouicha. A Petri Net Modelling of an Adaptive Learning Control Applied to an Electric Wheelchair. International Symposium on Computational Intelligence in Robotics and Automation, IEEE, Jun 2005, Espoo, Finland. pp.397-402, ⟨10.1109/CIRA.2005.1554309⟩. ⟨sic_01798077⟩

Collections

UNIV-TLN HANDIBIO
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More