Title
Biologically inspired SLAM using Wi-Fi Biologically inspired SLAM using Wi-Fi
Author
Faculty/Department
Faculty of Applied Economics
Faculty of Applied Engineering Sciences
Publication type
conferenceObject
Publication
[*]
Subject
Engineering sciences. Technology
Source (book)
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 14-18, 2014, Chicago, Ill., USA
ISSN
2153-0858
ISBN - Hoofdstuk
978-1-4799-6933-3
ISBN
978-1-4799-6931-9
ISI
000349834601134
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi- Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi- Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.
Full text (open access)
https://repository.uantwerpen.be/docman/irua/b3b8a1/8330.pdf
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