Model based estimation of ellipsoidal object using artificial electric sense. - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue The International Journal of Robotics Research Année : 2017

Model based estimation of ellipsoidal object using artificial electric sense.

Résumé

In this article we address the issue of shape estimation using electric sense inspired by the active electric fish. These fish can perceive their environment by measuring the perturbations in a self-generated electric field caused by nearby objects. The approach proceeded in three stages. Firstly the object was detected and its electric properties (insulator or conductor) identified. Secondly, the object was localized using the MUSIC (MUltiple SIgnal Classification) algorithm, which was originally developed to localize a radio wave emitter using a network of antennas. Thirdly, the shape estimation relied on the concept of generalized polarization tensor (GPT), which enabled modeling the electric response of an object polarized by an ambient electric field. We describe the implementation of the approach through numerous experiments. The system was able to estimate shape with an average error of 16%, and opened the way toward further improvements. In particular, self aligning the sensor with the ellipsoid through a reactive feedback makes the shape estimation errors drop to 10%.
Fichier principal
Vignette du fichier
IJRR2017.pdf (3.97 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01550624 , version 1 (29-06-2017)

Identifiants

Citer

Sylvain Lanneau, Frédéric Boyer, Vincent Lebastard, Stéphane Bazeille. Model based estimation of ellipsoidal object using artificial electric sense.. The International Journal of Robotics Research, 2017, ⟨10.1177/0278364917709942⟩. ⟨hal-01550624⟩
274 Consultations
134 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More