  In an era where autonomous robots increasingly inhabit public spaces, the
imperative for transparency and interpretability in their decision-making
processes becomes paramount. This paper presents the overview of a Robotic
eXplanation and Interpretability Engine (ROXIE), which addresses this critical
need, aiming to demystify the opaque nature of complex robotic behaviors. This
paper elucidates the key features and requirements needed for providing
information and explanations about robot decision-making processes. It also
overviews the suite of software components and libraries available for
deployment with ROS 2, empowering users to provide comprehensive explanations
and interpretations of robot processes and behaviors, thereby fostering trust
and collaboration in human-robot interactions.
