Publications in Scientific Journals:
B. Cakmak, D. Urup, F. Meyer, T. Pedersen, B. Fleury, F. Hlawatsch:
"Cooperative Localization for Mobile Networks: A Distributed Belief Propagation - Mean Field Message Passing Algorithm";
IEEE Signal Processing Letters,
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 measurement-related 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.
Belief propagation, mean field approximation, cooperative localization, distributed estimation, information projection, Kullback-Leibler-divergence, mobile agent network.
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.