Paper Info
Title
Mobile Robot Localization And Mapping With Uncertainty Using Scale-Invariant Visual Landmarks
Abstract
A key component of a mobile robot system is the ability to localize itself accurately and, simultaneously, to build a map of the environ- ment. Most of the existing algorithms are based on laser range find- ers, sonar sensors or artificial landmarks. In this paper, we describe a vision-based mobile robot localization and mapping algorithm, which uses scale-invariant image features as natural landmarks in unmodified environments. The invariance of these features to image translation, scaling and rotation makes them suitable landmarks for mobile robot localization and map building. With our Triclops stereo vision system, these landmarks are localized and robot ego-motion is estimated by least-squares minimization of the matched landmarks. Feature viewpoint variation and occlusion are taken into account by maintaining a view direction for each landmark. Experiments show that these visual landmarks are robustly matched, robot pose is es- timated and a consistent three-dimensional map is built. As image features are not noise-free, we carry out error analysis for the land- mark positions and the robot pose. We use Kalman filters to track these landmarks in a dynamic environment, resulting in a database map with landmark positional uncertainty. KEY WORDS—localization, mapping, visual landmarks, mobile robot
Year
DOI
Venue
2002
10.1177/027836402761412467
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
Keywords
Field
DocType
localization, mapping, visual landmarks, mobile robot
Image translation,Computer vision,Feature (computer vision),Stereopsis,Sonar,Artificial intelligence,Mobile robot navigation,Landmark,Robot,Mobile robot,Mathematics
Journal
Volume
Issue
ISSN
21
8
0278-3649
Citations 
PageRank 
References 
327
20.45
20
Authors
3
Search Limit
100327
Name
Order
Citations
PageRank
Stephen Se178692.81
D. G. Lowe2157181413.60
James J. Little32430269.59