Global Localization using Distinctive Visual Features

Global Localization using Distinctive Visual Features (2002)

by Stephen Se , David Lowe , Jim Little

Citations:

40 - 2 self

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Datum	Value	Source
TITLE	Global Localization using Distinctive Visual Features	user correction - Legacy Corrections
AUTHOR NAME	Stephen Se	user correction - Legacy Corrections
AUTHOR AFFIL	; MD Robotics; Brampton, Ontario L6S 4J3; ssemdrobotcs. ca	user correction - Legacy Corrections
AUTHOR ADDR	; 9445 Airport Road; Canada	user correction - Legacy Corrections
AUTHOR NAME	David Lowe	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science; University of British Co]umbia	user correction - Legacy Corrections
AUTHOR ADDR	Vancouver, B.C. V6T 1Z4, Canada	user correction - Legacy Corrections
AUTHOR NAME	Jim Little	user correction - Legacy Corrections
ABSTRACT	We have previously developed a mobile robot system which uses scale invariant visual landmarks to localize and simultaneously build a 3D map of the environment In this paper, we look at global localization, also known as the kidnapped robot problem, where the robot localizes itself globally, without any prior location estimate. This is achieved by matching distinctive landmarks in the current frame to a database map. A Hough Transform approach and a RANSAC approach for global localization are compared, showing that RANSAC is much more cjficicnt. Moreover, robust global localization can be achieved by matching a small sub-map of the local region built from multiple frames.	user correction - Legacy Corrections
YEAR	2002	user correction - Legacy Corrections
CITATIONS	15 found	ParsCit 1.0