Paper ID: 2501.07255

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

Issatay Tokmurziyev, Miguel Altamirano Cabrera, Luis Moreno, Muhammad Haris Khan, Dzmitry Tsetserukou

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.

Submitted: Jan 13, 2025