D. Fox, W. Burgard, H.Kruppa, and S. Thrun
A Probabilistic Approach to
Collaborative Multi-Robot Localization
Autonomous Robots, 2000
also appears in
Robot Teams: From Diversity to Polymorphism, A K Peters, 2002
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 possible if teams of heterogeneous robots collaborate during
localization.
Download
Full paper [.ps.gz]
(1164 kb, 25 pages)
There is also a larger version with high quality figures: [.ps.gz]
(2770 kb, 25 pages)
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 =
{Autonomous Robots},
YEAR
= {2000},
}