Attune: A Self-Annotation Tool for Understanding Robot Operator Attention Profiles

Deploying robot fleets in complex, real-world environments requires human operators to supervise multiple robots simultaneously. Managing operator attention is a fundamental challenge of designing multi-robot supervision interfaces, encompassing both feed layout and feed content (i.e., robot behavior design). Thus far, designers lack empirical guidance on the latter-how to change a robot's behavior to capture, sustain, or relinquish operator attention during multi-robot supervision. In our visio

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ethics.ai (12 August 2026), “Attune: A Self-Annotation Tool for Understanding Robot Operator Attention Profiles,” evidence record 19455, https://ethics.ai/record/19455 (originally published by arXiv cs.HC).

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