Topological Localization using Wi-Fi and Vision merged into FABMAP framework

Mathieu Nowakowski; Cyril Joly; Sébastien Dalibard; Nicolas Garcia; Fabien Moutarde

doi:10.1109/IROS.2017.8206171

Topological Localization using Wi-Fi and Vision merged into FABMAP framework

Mathieu Nowakowski ^{1, 2} Cyril Joly ¹ Sébastien Dalibard ² Nicolas Garcia ² Fabien Moutarde ¹

Abstract : — This paper introduces a topological localization algorithm that uses visual and Wi-Fi data. Its main contribution is a novel way of merging data from these sensors. By making Wi-Fi signature suited to FABMAP algorithm, it develops an early-fusion framework that solves global localization and kidnapped robot problem. The resulting algorithm is tested and compared to FABMAP visual localization, over data acquired by a Pepper robot in an office building. Several constraints were applied during acquisition to make the experiment fitted to real-life scenarios. Without any tuning, early-fusion surpasses the performances of visual localization by a significant margin: 94% of estimated localizations are less than 5m away from ground truth compared to 81% with visual localization.

Keywords : data fusion topological localization kidnapped robot low- cost sensors

Type de document :

Communication dans un congrès

Domaine :

Informatique [cs] / Vision par ordinateur et reconnaissance de formes [cs.CV]

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https://hal-mines-paristech.archives-ouvertes.fr/hal-01691920
Contributeur : Fabien Moutarde <>
Soumis le : mercredi 24 janvier 2018 - 14:03:48
Dernière modification le : lundi 12 novembre 2018 - 11:03:37
Document(s) archivé(s) le : jeudi 24 mai 2018 - 18:35:28

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