Failure Detection for Laser-based SLAM in Urban and Peri-Urban Environments

Abstract : Simultaneous Localization And Mapping (SLAM) is considered as one of the key solutions for making mobile robots truly autonomous. Based mainly on perceptive information, the SLAM concept is assumed to solve localization and provide a map of the surrounding environment simultaneously. In this paper, we study SLAM limitations and we propose an approach to detect a priori potential failure scenarios for 2D laser-based SLAM methods. Our approach makes use of raw sensor data, which makes it independent of the underlying SLAM implementation, to extract a relevant descriptors vector. This descriptors vector is then used together with a decision-making algorithm to detect failure scenarios. Our approach is evaluated using different decision algorithms through three realistic experiments.
Type de document :
Communication dans un congrès
ITSC 2017 - IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan. pp.1-7, 〈http://www.itsc2017.org/〉
Liste complète des métadonnées

Littérature citée [26 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01623394
Contributeur : Anne Verroust-Blondet <>
Soumis le : mercredi 25 octobre 2017 - 11:37:48
Dernière modification le : jeudi 26 octobre 2017 - 13:56:37
Document(s) archivé(s) le : vendredi 26 janvier 2018 - 14:13:25

Fichier

Could_SLAM_fail_ITSC_2017_auth...
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01623394, version 1

Collections

Citation

Zayed Alsayed, Guillaume Bresson, Anne Verroust-Blondet, Fawzi Nashashibi. Failure Detection for Laser-based SLAM in Urban and Peri-Urban Environments. ITSC 2017 - IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan. pp.1-7, 〈http://www.itsc2017.org/〉. 〈hal-01623394〉

Partager

Métriques

Consultations de la notice

160

Téléchargements de fichiers

108