HEXAR: a Hierarchical Explainability Architecture for Robots
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.
Evidence notes
- Experiments use TIAGo as the physical evaluation platform.
- The reported results provide an independent evaluation on TIAGo hardware.
Company context
Develops service and humanoid robots for research, industrial, and public-facing environments, with a focus on modular platforms and long-term deployment in real-world settings.