Mapping Human Grasping to 3-Finger Grippers: A Deep Learning Perspective
Published in 32nd International Conference on Electrical Engineering (ICEE 2024), 2024
We present a deep learning approach to map human grasping patterns to 3-finger robotic grippers. A dataset was generated using human hand features, with pre-processing steps employing MediaPipe to extract precise finger coordinates. The model was trained using object detection and computer vision techniques to identify optimal grasping points for robotic manipulation.
Recommended citation: F. Naeinian, E. Balazadeh, M. Tale Masouleh, 'Mapping Human Grasping to 3-Finger Grippers: A Deep Learning Perspective,' 2024 32nd International Conference on Electrical Engineering (ICEE), pp. 1–7, 2024.
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