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原文摘要

Legibility in human-robot interaction (HRI) is often described as the property of robot motion that enables an observer to confidently and quickly infer the robot's intent. Mature frameworks exist for generating legible motion in front of static observers, typically by making the robot's destination apparent as early as possible. Social robot navigation in public spaces, however, presents a different challenge: pedestrians are themselves in motion, often with divided attention, and must coordinate with the robot in real time. In such encounters, where the robot is ultimately headed may matter less to a pedestrian than how it intends to pass them. This raises two questions: which aspect of intent should legible motion convey, and does legibility remain beneficial when pedestrians are not fully attentive to the robot? We address these questions in the ubiquitous and demanding scenario of hallway navigation, through two controlled user studies comparing multiple legibility formulations implemented within a shared model predictive control framework. Study 1 (N = 45) compares destination-based and passing-side intent representations, showing that the latter, particularly when adaptively updated, allows for smoother human motion and is perceived as more competent and less mentally and physically demanding than the former. Study 2 (N = 45) examines the effect of pedestrian attention, demonstrating that legible motion supports smooth human motion even under distraction, although this benefit is not consistently reflected in subjective ratings. Together, these findings suggest that effective legible motion in social robot navigation benefits from interaction-level intent representations that support coordination, with some effects persisting even when human attention is divided.