  This paper introduces WOLF, a C++ estimation framework based on factor graphs
and targeted at mobile robotics. WOLF can be used beyond SLAM to handle
self-calibration, model identification, or the observation of dynamic
quantities other than localization. The architecture of WOLF allows for a
modular yet tightly-coupled estimator. Modularity is enhanced via reusable
plugins that are loaded at runtime depending on application setup. This setup
is achieved conveniently through YAML files, allowing users to configure a wide
range of applications without the need of writing or compiling code. Most
procedures are coded as abstract algorithms in base classes with varying levels
of specialization. Overall, all these assets allow for coherent processing and
favor code re-usability and scalability. WOLF can be used with ROS, and is made
publicly available and open to collaboration.
