Abstract
We propose a hybrid message passing method
for distributed cooperative localization and tracking of mobile
agents. Belief propagation and mean field message passing are
employed for, respectively, the motion-related and measurementrelated
part of the factor graph. Using a Gaussian belief approximation,
only three real values per message passing iteration
have to be broadcast to neighboring agents. Despite these very
low communication requirements, the estimation accuracy can
be comparable to that of particle-based belief propagation.
for distributed cooperative localization and tracking of mobile
agents. Belief propagation and mean field message passing are
employed for, respectively, the motion-related and measurementrelated
part of the factor graph. Using a Gaussian belief approximation,
only three real values per message passing iteration
have to be broadcast to neighboring agents. Despite these very
low communication requirements, the estimation accuracy can
be comparable to that of particle-based belief propagation.
Originalsprog | Engelsk |
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Tidsskrift | I E E E Signal Processing Letters |
Vol/bind | 23 |
Udgave nummer | 6 |
Sider (fra-til) | 828 - 832 |
ISSN | 1070-9908 |
DOI | |
Status | Udgivet - 5 apr. 2016 |