Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters

arXiv cs.AI / 4/20/2026

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Key Points

  • The paper argues that uncertainty, vagueness, and ambiguity in human-robot interaction (HRI) are frequently conflated due to inconsistent definitions and terminology across prior studies.
  • It proposes a consistent conceptual framework by first examining dictionary meanings, then analyzing how these concepts differ and relate specifically within HRI.
  • The authors illustrate the distinctions and relationships with concrete examples to make the conceptual distinctions practically clearer.
  • They claim that this shared foundation improves empirical comparability and enables the design of new methods and more reliable evaluation of existing HRI methodologies.

Abstract

Uncertainty, vagueness, and ambiguity are closely related and often confused concepts in human-robot interaction (HRI). In earlier studies, these concepts have been defined in contradictory ways and described using inconsistent terminology. This conceptual confusion and lack of terminological consistency undermine empirical comparability, thereby slowing the accumulation of theory. Consequently, consistent concepts that clarify these challenges, including their definitions, distinctions, and interrelationships, are needed in HRI. To address this lack of clarity, this paper proposes a consistent conceptual foundation for the challenges of uncertainty, vagueness, and ambiguity in HRI. First, we examine the meanings of these three terms in dictionaries. We then analyze the nature of their distinctions and interrelationships within the context of HRI. We further illustrate these characteristics through examples. Finally, we demonstrate how this consistent conceptual foundation facilitates the design of novel methods and the evaluation of existing methodologies for these phenomena.