D. Fox, W. Burgard, H.Kruppa, and S. Thrun
A Probabilistic Approach toCollaborative
Multi-Robot Localization
Autonomous Robots, 2000
Abstract
This paper presents a statistical algorithm for collaborative mobile robot
localization. Our approach uses a sample-based version of Markov localization,
capable of localizing mobile robots in an any-time fashion. When teams of
robots localize themselves in the same environment, probabilistic methods
are employed to synchronize each robot's belief whenever one robot detects
another. As a result, the robots localize themselves faster, maintain higher
accuracy, and high-cost sensors are amortized across multiple robot platforms.
The technique has been implemented and tested using two mobile robots equipped
with cameras and laser range-finders for detecting other robots. The results,
obtained with the real robots and in series of simulation runs, illustrate
drastic improvements in localization speed and accuracy when compared to
conventional single-robot localization. A further experiment demonstrates
that under certain conditions, successful localization is only possibleif
teams of heterogeneous robots collaborate during localization.
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Bibtex
@Article{Fox00Pro,
AUTHOR = {Fox, D. and Burgard, W. and Kruppa, H. and Thrun,
S.},
TITLE = {A Probabilistic Approach to Collaborative Multi-Robot
Localization},
JOURNAL = {AutonomousRobots},
YEAR = {2000},
NOTE = {To appear}
}