NDLI: A comparison of global localization algorithms for planetary exploration

Content Provider	IEEE Xplore Digital Library
Author	Furgale, P. Carle, P. Barfoot, T.D.
Copyright Year	2010
Description	Author affiliation: University of Toronto Institute for Aerospace Studies, 4925 Dufferin Street, Canada M3H 5T6 (Furgale, P.; Carle, P.; Barfoot, T.D.)
Abstract	Global localization of a planetary-exploration rover in the absence of a satellite-based global positioning system (GPS) is still an open problem. Although a satellite network is not available for localization around any near-term exploration targets, topographic maps derived from satellite imagery are available. This has spurred the development of several algorithms that perform global localization by matching data collected from onboard sensors to a global digital elevation map (DEM). This paper reviews two of these algorithms—Multiple-frame Odometry-compensated Global Alignment (MOGA) and VIsual Position Estimation for Rovers (VIPER)—and compares their performance on a common dataset, collected in a planetary analog environment. The comparison demonstrates the common factors limiting the performance of these algorithms, but also highlights the benefits and drawbacks of each method. Overall, the MOGA algorithm performed significantly better; however, running both algorithms is seen to be the best option as the computational cost of VIPER is low and it may succeed in some situations wherein MOGA will fail.
Starting Page	4964
Ending Page	4969
File Size	1815565
Page Count	6
File Format	PDF
ISBN	9781424466740
ISSN	21530866
e-ISBN	9781424466764
DOI	10.1109/IROS.2010.5649051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-18
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laser radar Extraterrestrial measurements Position measurement Estimation Satellites Feature extraction Uncertainty
Content Type	Text
Resource Type	Article

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