A framework for inference in Dynamic Bayesian Networks
Description
The Bayesian Filtering Library (BFL) provides an application independent
framework for inference in Dynamic Bayesian Networks, i.e., recursive
information processing and estimation algorithms based on Bayes' rule, such as
(Extended) Kalman Filters, Particle Filters, etc. These algorithms can, for
example, be run on top of the Realtime Services, or be used for estimation in
Kinematics & Dynamics applications.
