Title
Vision-based global localization and mapping for mobile robots
Abstract
We have previously developed a mobile robot system which uses scale-invariant visual landmarks to localize and simultaneously build three-dimensional (3-D) maps of unmodified environments. In this paper, we examine global localization, where the robot localizes itself globally, without any prior location estimate. This is achieved by matching distinctive visual 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 efficient for matching specific features, but much worse for matching nonspecific features. Moreover, robust global localization can be achieved by matching a small submap of the local region built from multiple frames. This submap alignment algorithm for global localization can be applied to map building, which can be regarded as alignment of multiple 3-D submaps. A global minimization procedure is carried out using the loop closure constraint to avoid the effects of slippage and drift accumulation. Landmark uncertainty is taken into account in the submap alignment and the global minimization process. Experiments show that global localization can be achieved accurately using the scale-invariant landmarks. Our approach of pairwise submap alignment with backward correction in a consistent manner produces a better global 3-D map.
Year
DOI
Venue
2005
10.1109/TRO.2004.839228
IEEE Transactions on Robotics
Keywords
Field
DocType
Mobile robots,Simultaneous localization and mapping,Robustness,Uncertainty,Intelligent robots,Buildings,Spatial databases,Visual databases,Computer vision,Intelligent systems
Motion planning,Computer vision,RANSAC,Hough transform,Robustness (computer science),Artificial intelligence,Landmark,Simultaneous localization and mapping,Robot,Mobile robot,Mathematics
Journal
Volume
Issue
ISSN
21
3
1552-3098
Citations 
PageRank 
References 
133
6.31
25
Authors
3
Search Limit
100133
Name
Order
Citations
PageRank
S. Se116714.16
D. G. Lowe2157181413.60
James J. Little32430269.59