Explainable Artificial Intelligence (XAI) is essential in C-HRI for c-hri transparency and trust. Humans must understand why a robot takes certain actions. Explanation supports confidence and informed decision-making.
C-HRI systems generate explanations through visual cues, verbal descriptions, or behavior-based feedback. These explanations clarify system intentions and reasoning processes. Clear communication reduces uncertainty.
Explainability is particularly important in safety-critical environments. Users must quickly assess whether a robot’s decision is appropriate. Transparent systems enable rapid intervention when necessary.
Cognitive models help structure explanations in human-understandable terms. Robots map internal reasoning to familiar concepts and goals. This alignment improves comprehension.
Through XAI, C-HRI systems become more trustworthy and accountable. Humans remain informed partners in collaboration. Explainability supports ethical and responsible interaction.