Force-Torque Sensor Disturbance Observer using Deep Learning

Kamal Mohy El Dine 1 Jose Sanchez 1 Juan Corrales Youcef Mezouar 1 Jean-Christophe Fauroux 1
1 IP - Institut Pascal - Clermont Auvergne
Abstract : Robots executing force controlled tasks require accurate perception of the applied force in order to guarantee precision. However, dynamic motions generate non-contact forces due to the inertia. These non-contact forces can be regarded as disturbances to be removed such that only the forces generated by contacts with the environment remain. This paper presents an observer based on a recurrent neural network that estimates the non-contact forces measured by a force-torque sensor attached at the end-effector of a robotic arm. The approach is proven to also work with an external load attached to the robotic arm. The recurrent neural network observer uses signals from the joint encoders of the robotic arm and a low-cost inertial measurement unit to estimate the wrenches (i.e. forces and torques) generated due to gravity, inertia, centrifugal and Coriolis forces. The accuracy of the proposed observer is experimentally evaluated by comparing the measurements of the attached force-torque sensor to the observer's non-contact forces estimation. Additionally, the pure contact force estimation is evaluated against an external force-torque sensor.
Type de document :
Communication dans un congrès
2018 International Symposium on Experimental Robotics (ISER 2018), Nov 2018, Buenos Aires, Argentina. 〈http://iser2018.org/〉
Liste complète des métadonnées
https://hal.archives-ouvertes.fr/hal-01921495
Contributeur : Jose Manuel Sanchez Loza <>
Soumis le : mardi 13 novembre 2018 - 18:53:44
Dernière modification le : mardi 27 novembre 2018 - 01:20:56
Document(s) archivé(s) le : jeudi 14 février 2019 - 16:44:21

Fichier

iser2018.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01921495, version 1

Collections

INSTITUT_PASCAL | SIGMA-CLERMONT | PRES_CLERMONT

Citation

Kamal Mohy El Dine, Jose Sanchez, Juan Corrales, Youcef Mezouar, Jean-Christophe Fauroux. Force-Torque Sensor Disturbance Observer using Deep Learning. 2018 International Symposium on Experimental Robotics (ISER 2018), Nov 2018, Buenos Aires, Argentina. 〈http://iser2018.org/〉. 〈hal-01921495〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

26

Téléchargements de fichiers

62

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD