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Topological Localization using Wi-Fi and Vision merged into FABMAP framework
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.
Littérature citée [19 références]
https://hal-mines-paristech.archives-ouvertes.fr/hal-01691920
Contributeur : Fabien Moutarde <>
Soumis le : mercredi 24 janvier 2018 - 14:03:48
Dernière modification le : vendredi 6 mars 2020 - 01:07:02
Document(s) archivé(s) le : jeudi 24 mai 2018 - 18:35:28
Contributeur : Fabien Moutarde <>
Soumis le : mercredi 24 janvier 2018 - 14:03:48
Dernière modification le : vendredi 6 mars 2020 - 01:07:02
Document(s) archivé(s) le : jeudi 24 mai 2018 - 18:35:28
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