HEXAR: a Hierarchical Explainability Architecture for Robots

Evidence notes

• As robotic systems become increasingly complex, the need for explainable decision-making becomes critical. Existing explainability approaches in robotics typically either focus on individual modules, which can be difficult to query from the perspective of high-level behaviour, or employ monolithic approaches, which do not exploit the modularity of robotic architectures.
• The work is explicitly tied to TIAGo, making the product binding high confidence.
• The artifact adds external research coverage for TIAGo beyond company-authored releases.