NDLI: Vision and sonar sensor fusion for mobile robot localization in aliased environments

Content Provider	IEEE Xplore Digital Library
Author	Zingaretti, P. Frontoni, E.
Copyright Year	2006
Description	Author affiliation: Dipt. di Ingegneria Informatica, Univ. Politecnica delle Marche, Ancona (Zingaretti, P.; Frontoni, E.)
Abstract	Monte Carlo localization (MCL) is a common method for self-localization of a mobile robot under the assumption that a map of the environment is available. Original implementations used range sensors like laser scanners and sonar sensors. Recently, localization approaches using vision sensors have been developed with good results. In this paper we compare vision-based with sonar-based MCL approaches in terms of localization accuracy. In particular, we show how in an environment with high perceptual aliasing like our department both approaches bear certain weaknesses while by combining vision and sonar sensors the respective localization errors decrease and overall accuracy is improved
Sponsorship	IEEE Intelligent Transportation Syst. Soc
Starting Page	1
Ending Page	6
File Size	360130
Page Count	6
File Format	PDF
ISBN	0780397215
DOI	10.1109/MESA.2006.296971
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-13
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	vision sensors Robot vision systems Sensor fusion autonomous robots Sonar navigation sensor fusion Mobile robots robot localization and navigation motion and sensor modeling Mobile robotics sonar sensors Robot sensing systems Cameras Robot localization Particle filters Laser fusion State estimation
Content Type	Text
Resource Type	Article

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