Visual Proactivity: Enhancing Human-Robot Collaboration Through Intent Communication

2026-09-18

AI Summary

研究通过视觉反馈方式提升机器人主动沟通意图的能力，以增强人机协作的透明度与流畅性，实验验证了该方法在人机传递物品场景中能有效提高配合度。

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.

Problem

• visual proactivity
• human-robot collaboration
• intent communication
• transparency
• fluency

Innovation

• visual proactivity
• human-robot collaboration
• intent communication