WOLF: A Modular Estimation Framework for Robotics Based on Factor Graphs

摘要

This letter introduces <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Wolf</small> , a C++ estimation framework based on factor graphs and targeted at mobile robotics. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Wolf</small> can be used beyond SLAM to handle self-calibration, model identification, or the observation of dynamic quantities other than localization. The architecture of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Wolf</small> 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. <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Wolf</small> can be used with <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ROS</small> , and is made publicly available and open to collaboration.