Publication
Title
Biologically inspired SLAM using Wi-Fi
Author
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.
Language
English
Source (book)
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 14-18, 2014, Chicago, Ill., USA
Publication
2014
ISSN
2153-0858
ISBN
978-1-4799-6931-9
978-1-4799-6933-3
Volume/pages
p. 1804-1811
ISI
000349834601134
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 30.09.2014
Last edited 12.11.2017
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