Visual Proactivity: Enhancing Human-Robot Collaboration through Intent Communication

Abstract

As robots transition from performing repetitive tasks to collaborating with humans, understanding human intent becomes crucial to effective interaction. Anticipation enables robots to predict human actions, while proactivity allows them to take initiative and guide human behavior toward optimal outcomes. Although research has largely focused on how robots infer and respond to human intentions, less attention has been paid to how robots communicate their own intent. This paper introduces visual proactivity, a novel, simple yet effective approach that enables robots to communicate their intentions through visual feedback, influencing human behavior and enhancing transparency and fluency. We develop and evaluate proactive robotic behaviors in a human-to-robot handover scenario, where a user study validates human perception of reactive, anticipatory, and proactive behaviors. The results demonstrate that effective visual proactivity fosters better alignment and coordination, paving the way for more intuitive human-robot collaboration.