Towards Continuous Identification of Passive Human Joint Impedance Using Physical Human-Robot Interaction System - Université Polytechnique des Hauts-de-France Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Towards Continuous Identification of Passive Human Joint Impedance Using Physical Human-Robot Interaction System

Résumé

The identification of human joint impedance is necessary for various applications, such as improving rehabilitation efficiency or monitoring the human operator's state (fatigue, stress). To this end, in this paper we combine robot's payload identification methods with sliding window recursive least squares algorithm allowing a continuous identification of the varying human joint model without the need for external sensors. We also propose a threshold for detecting fake changes in the identified model parameters due to numerical issues. The presented approach is validated by simulations and experiments using elastic rubber bands representing a simplified passive human joint model attached to a one degree of freedom robotic system. Comparison with simple recursive least squares shows that the proposed method is promising, as it converges to the new parameter in a single window length, whereas the other method takes much longer. In addition, it distinguishes real from fake changes depending on the validity of the used model.
Fichier sous embargo
Fichier sous embargo
0 1 3
Année Mois Jours
Avant la publication
vendredi 21 juin 2024
Fichier sous embargo
vendredi 21 juin 2024
Connectez-vous pour demander l'accès au fichier

Dates et versions

hal-04350680 , version 1 (21-12-2023)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

Citer

Bilal Tout, Jason Chevrie, Antoine Dequidt, Laurent Vermeiren. Towards Continuous Identification of Passive Human Joint Impedance Using Physical Human-Robot Interaction System. 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Oct 2023, Detroit (MI), United States. pp.4129-4134, ⟨10.1109/IROS55552.2023.10341372⟩. ⟨hal-04350680⟩
26 Consultations
4 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More