The proverb ``see something, say something'' captures a core responsibility of autonomous mobile robots in safety-critical situations: when they detect a hazard, they must communicate--and do so quickly. In emergency scenarios, delayed or miscalibrated responses directly increase the time to action and the risk of damage. We argue that a systematic context-sensitive assessment of the criticality level, time sensitivity, and feasibility of mitigation is necessary for AMRs to reduce time to action and respond effectively. This paper presents a framework in which VLM/LLM-based perception drives adaptive message generation, for example, a knife in a kitchen produces a calm acknowledgment; the same object in a corridor triggers an urgent coordinated alert. Validation in 60+ runs using a patrolling mobile robot not only empowers faster response, but also brings user trusts to 82\% compared to fixed-priority baselines, validating that structured criticality assessment improves both response speed and mitigation effectiveness.
@article{arxiv.2603.28901,
title = {See Something, Say Something: Context-Criticality-Aware Mobile Robot Communication for Hazard Mitigations},
author = {Bhavya Oza and Devam Shah and Ghanashyama Prabhu and Devika Kodi and Aliasghar Arab},
journal= {arXiv preprint arXiv:2603.28901},
year = {2026}
}