Paper Info
Title
Swarm-supported outdoor localization with sparse visual data
Abstract
The localization of mobile systems with video data is a challenging field in robotic vision research. Apart from support technologies like a GPS, a self-sufficient visual system is desirable. We introduce a new heuristic approach to outdoor localization in a scenario with sparse visual data and without odometry readings. Localization is interpreted as an optimization problem, and a swarm-based optimization method is adapted and applied, remaining independent of the specific visual feature type. The new method obtains similar or better localization results in our experiments while requiring only two-thirds of the number of image comparisons, indicating an overall speed-up by 25%.
Year
DOI
Venue
2010
10.1016/j.robot.2009.09.012
EMCR
Keywords
DocType
Volume
Outdoor robotics,Robot vision,Visual localization,Swarm intelligence,Particle swarm optimization
Journal
58
Issue
ISSN
Citations 
2
0921-8890
5
PageRank 
References 
Authors
0.82
25
3
Name
Order
Citations
PageRank
Marcel Kronfeld1746.67
Christian Weiss2866.62
Andreas Zell31419137.58