The Bayesian Filtering Library development team is pleased to announce the first bug-fix release of the Bayesian Filtering Library v0.6.
You can download this release from and read the installation instructions online at (also reachable through the orocos website).

The Bayesian Filtering Library development team is pleased to announce the 0.6.0 release of BFL.
You can download this release from here and read the installation instructions online (also reachable through the orocos website).

This release includes support for lti, boost and newmat as matrix library and lti and boost as random number generator.
A new feature is the backward filter and smoother algorithm and the CPPUnit tests.
Furthermore for the first time, a step-by-step installation guide is available for Visual Studio on Windows.

The Bayesian Filtering Library development team is pleased to announce the 0.6.0 prerlease of BFL.
You can download this prerelease from

and read the installation instructions on
(also reachable through the orocos website)

This release includes support for lti, boost and newmat as matrix library and lti and boost as random number generator.
A new feature is the backward filter and smoother algorithm and the CPPUnit tests.

New Ubuntu/Debian packages of the latest BFL trunk with the integrated MatrixWrapper are available in a new repository. To upgrade to these newest packages, follow the instructions in the download - packages section. The old BFL Ubuntu/Debian packages will remain in the current repository for a while.

BFL was moved from its original subversion repository, to the Orocos subversion repository. Because this is a different repository, it is not possible to automatically migrate your checks out copy of BFL. You will need to store the local changes in your copy of the old repository (svn diff), then check out the new BFL trunk (svn co http://svn.mech.kuleuven.be/repos/orocos/trunk/bfl), and finally apply your changes to the new trunk. Also check out the updated installation instructions.

Over the past week, BFL has followed RTT, KDL and OCL in their move from a build system based on autotools, to a build system based on cmake. This should also make it easier to build BFL for Windows. The installation instructions for linux have been updated. If anyone tries a Windows build, we're interested in your experiences.

BFL relies on the MatrixWrapper to make itself independent of the underlying matrix library (Lti or Newmat). In the past BFL and the MatrixWrapper where two separate projects. We now merged the MatrixWrapper into the BFL, which decreases maintenance efforts and makes it easier to install BFL.

Welcome on the new homepage of BFL. From now on, information about BFL will appear on these pages, to stress the integration possibilities of BFL with the Kinematics and Dynamics Library (KDL) and the orocos Real-Time Toolkit.

The integration of these 3 libraries allows you to create smart components for robotics and automation!