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35

ICPR
2008
IEEE

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On the scalability of robot localization using high-dimensional features

14 years 5 months ago

On the scalability of robot localization using high-dimensional features

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This study provides an investigation of scalability of mobile robot localization. In recent years, inference algorithms based on map-matching have proved their superior performance in large-scale environments. In this paper, the scalability is augmented by an ANN retrieval of high-dimensional descriptive features. The proposed algorithm is then exhaustively evaluated using largesize real maps, including over 100K feature maps.

Takeshi Ueda, Kanji Tanaka

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Computer Vision | ICPR 2008 | Largesize Real Maps | Mobile Robot Localization | Scalability |

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Added	30 May 2010
Updated	30 May 2010
Type	Conference
Year	2008
Where	ICPR
Authors	Takeshi Ueda, Kanji Tanaka

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