GazeGrasp: DNN-Driven Robotic Grasping with Wearable Eye-Gaze Interface
Issatay Tokmurziyev, Miguel Altamirano Cabrera, Luis Moreno, Muhammad, Haris Khan, Dzmitry Tsetserukou

TL;DR
GazeGrasp is a gaze-based robotic manipulation system that enables users with motor impairments to control robots through eye-gaze and gestures, improving accessibility and task efficiency.
Contribution
The paper introduces GazeGrasp, a novel eye-gaze interface integrating eye tracking, object detection, and robot control for assistive manipulation.
Findings
Magnetic snapping reduces gaze alignment time.
Task efficiency improved by 31%.
System is robust and user-friendly.
Abstract
We present GazeGrasp, a gaze-based manipulation system enabling individuals with motor impairments to control collaborative robots using eye-gaze. The system employs an ESP32 CAM for eye tracking, MediaPipe for gaze detection, and YOLOv8 for object localization, integrated with a Universal Robot UR10 for manipulation tasks. After user-specific calibration, the system allows intuitive object selection with a magnetic snapping effect and robot control via eye gestures. Experimental evaluation involving 13 participants demonstrated that the magnetic snapping effect significantly reduced gaze alignment time, improving task efficiency by 31%. GazeGrasp provides a robust, hands-free interface for assistive robotics, enhancing accessibility and autonomy for users.
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Taxonomy
TopicsGaze Tracking and Assistive Technology · Hand Gesture Recognition Systems · Robot Manipulation and Learning
