GEAR: Gaze-Enabled Human-Robot Collaborative Assembly

2025-07-25

AI Summary

To address low human-robot collaboration efficiency and high operator physical workload in complex, dynamic assembly tasks, this paper proposes an eye-tracking-based visual-guidance method for human-robot collaborative assembly. It pioneers real-time eye-gaze interaction in assembly scenarios, integrating gaze-intent recognition with service robot control to establish a contactless, low-cognitive-load closed-loop collaboration system. In a comparative study with 30 participants, the proposed method significantly reduced operator workload compared to conventional touch interfaces (p < 0.01), maintained higher task completion rates and superior response timeliness—especially under high-complexity conditions—and improved subjective usability and naturalness of interaction. The core contributions are: (1) the first implementation of real-time eye-driven parsing of assembly intent; and (2) empirical validation of the effectiveness and practicality of contactless interaction in industrial human-robot collaboration.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Interaction Techniques and Devices
• Computer Vision: Motion & Tracking

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

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

Problem

• Enhancing human-robot collaboration in complex assembly tasks
• Reducing physical demand in assembly using gaze-enabled systems
• Improving user experience in human-robot interaction for precise operations

Innovation

• Gaze-enabled system for human-robot collaboration
• Robot assists by fetching parts autonomously
• Reduces physical demand with gaze interaction