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.
@article{arxiv.2501.07255,
title = {GazeGrasp: DNN-Driven Robotic Grasping with Wearable Eye-Gaze Interface},
author = {Issatay Tokmurziyev and Miguel Altamirano Cabrera and Luis Moreno and Muhammad Haris Khan and Dzmitry Tsetserukou},
journal= {arXiv preprint arXiv:2501.07255},
year = {2025}
}
Comments
Accepted to: IEEE/ACM International Conference on Human-Robot Interaction (HRI 2025)