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

arXiv: https://arxiv.org/abs/2604.15339 · HTML: https://mlsanity.com/paper/2604.15339/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 30 references that are in the map.
- First posted on arXiv 10 Mar 2026.

## Builds on (most cited first, 14 of 14)

- [Do As I Can, Not As I Say: Grounding Language in Robotic Affordances](https://mlsanity.com/paper/2204.01691/) (2022)
- [A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges](https://mlsanity.com/paper/2011.06225/) (2020)
- [Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners](https://mlsanity.com/paper/2307.01928/) (2023)
- [Robot Learning in the Era of Foundation Models: A Survey](https://mlsanity.com/paper/2311.14379/) (2023)
- [When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans](https://mlsanity.com/paper/2001.04377/) (2020)
- [Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interaction](https://mlsanity.com/paper/1907.02426/) (2019)
- [The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning](https://mlsanity.com/paper/2405.03164/) (2024)
- [Active Uncertainty Reduction for Human-Robot Interaction: An Implicit Dual Control Approach](https://mlsanity.com/paper/2202.07720/) (2022)
- [Robotic Task Ambiguity Resolution via Natural Language Interaction](https://mlsanity.com/paper/2504.17748/) (2025)
- [Talk-to-Resolve: Combining scene understanding and spatial dialogue to resolve granular task ambiguity for a collocated robot](https://mlsanity.com/paper/2111.11099/) (2021)
- [Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning](https://mlsanity.com/paper/2406.09988/) (2024)
- [Advancing Household Robotics: Deep Interactive Reinforcement Learning for Efficient Training and Enhanced Performance](https://mlsanity.com/paper/2405.18687/) (2024)
- [LLM-based ambiguity detection in natural language instructions for collaborative surgical robots](https://mlsanity.com/paper/2507.11525/) (2025)
- [Perspective-corrected Spatial Referring Expression Generation for Human-Robot Interaction](https://mlsanity.com/paper/2104.01558/) (2021)

## Abstract (arXiv)

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.