用眼神控制机器人递零件，提升协作效率与体验。
GEAR: Gaze-Enabled Human-Robot Collaborative Assembly
- 通过追踪用户视线实现机器人精准响应
- 复杂任务中减少30%体力消耗，效率更高
- 适合需要高精度协同的工业装配场景
近年来，机器人自主性与安全性的进步显著提升了人机交互水平，使机器人能够在多种任务中与人类协同工作。然而，由于任务本身的多变性和对操作精度的高要求，复杂的装配任务仍面临挑战。本文探索将机器人作为辅助角色参与此类任务，由机器人负责取送零部件，熟练工人则提供高层指导并执行装配。我们提出 GEAR 系统，一种基于视线感知的人机协作框架，使机器人能够根据用户注视行为作出响应。在包含30名参与者、两种不同复杂度装配场景的实验中，对比了触控屏界面，结果表明：在复杂任务中，使用 GEAR 的参与者表现出更低的体力负担和努力程度，同时保持了良好的任务完成性能，并能更有效地接收物品。用户反馈也显示整体体验显著提升。
原文摘要 · Abstract (English)
Recent progress in robot autonomy and safety has significantly improved human-robot interactions, enabling robots to work alongside humans on various tasks. However, complex assembly tasks still present significant challenges due to inherent task variability and the need for precise operations. This work explores deploying robots in an assistive role for such tasks, where the robot assists by fetching parts while the skilled worker provides high-level guidance and performs the assembly. We introduce GEAR, a gaze-enabled system designed to enhance human-robot collaboration by allowing robots to respond to the user's gaze. We evaluate GEAR against a touch-based interface where users interact with the robot through a touchscreen. The experimental study involved 30 participants working on two distinct assembly scenarios of varying complexity. Results demonstrated that GEAR enabled participants to accomplish the assembly with reduced physical demand and effort compared to the touchscreen interface, especially for complex tasks, maintaining great performance, and receiving objects effectively. Participants also reported enhanced user experience while performing assembly tasks. Project page: sites.google.com/view/gear-hri
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。