GazeGrasp: DNN-Driven Robotic Grasping with Wearable Eye-Gaze Interface

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.