Eagle-Leg Biomechanics for Enhanced Gesture-Based Robotic Gripping

A bio-inspired robotic gripper that mimics the biomechanics of an eagle's leg is presented in this research to improve dexterity, flexibility, and energy efficiency in gripping. A CNN-based gesture detection system and a tendon-driven actuation mechanism were combined in the design, which also used MediaPipe for real-time hand tracking to facilitate smooth human-robot interaction. An average gesture recognition accuracy of over 95% (precision 0.91) was shown in the experimental results, guaranteeing accurate mapping of human input to robotic operations. According to force and stability studies, the eagle-inspired gripper successfully balanced and securely grasped a 300 g cylindrical object by utilizing a minimal grip angle of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$30^{\circ}$</tex> and optimum string tensions <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\boldsymbol{T}_{1}=3.4 kgm/ s^{2}, T_{2}=2.82 \ kg \cdot m / \mathrm{s}^{2})$</tex>. The system can handle a variety of objects, including delicate and oddly shaped ones, because it also successfully inhibits objects from sliding through a balanced force equilibrium. The results demonstrate the gripper's superiority over traditional designs and its durability in biomedical handling, industrial automation, and agriculture.