GazeGrasp: DNN-Driven Robotic Grasping with Wearable Eye-Gaze Interface
Tokmurziyev, Issatay, Cabrera, Miguel Altamirano, Moreno, Luis, Khan, Muhammad Haris, Tsetserukou, Dzmitry
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jan-14-2025
- Genre:
- Research Report (1.00)
- Technology:
- Information Technology > Artificial Intelligence > Robots (1.00)