  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.
