As autonomous robots become more prevalent in public environments, ensuring the transparency and interpretability of their decision-making processes is crucial to building trust and promoting effective human-robot collaboration. The European Union’s Artificial Intelligence Act (AI Act) reinforces these priorities by establishing a regulatory framework that emphasizes accountability, explainability, and ethical governance in AI systems. In this context, this paper presents the Robotic eXplanation and Interpretability Engine (ROXIE) a framework specifically designed to address these challenges by clarifying and making understandable the complex behaviors exhibited by autonomous robots. ROXIE defines the essential requirements for explainability and interpretability while leveraging the tools, components, and libraries available within the ROS 2 ecosystem to implement these capabilities in a practical and scalable manner. By providing clear, accessible, and context-aware explanations of robotic decision-making, ROXIE bridges the gap between technical innovation and regulatory compliance. Ultimately, it contributes to the responsible deployment of autonomous systems, fostering transparency, trust, and societal acceptance in the emerging era of explainable robotics.