An Anthropomorphic Robotic Finger With Innate Human-Finger-Like Biomechanical Advantages Part II: Flexible Tendon Sheath and Grasping Demonstration

Abstract

The human hand has a fantastic ability to interact with various objects in the dynamic unstructured environment of our daily activities. We believe that this outstanding performance benefits a lot from the unique biological features of the hand musculoskeletal system. In Part I of this article, a bio-inspired anthropomorphic robotic finger was developed, based on which two human-finger-like biomechanical advantages were elaborately investigated, including the anisotropic variable stiffness associated with the ligamentous joints and the enlarged feasible force space associated with the reticular extensor mechanisms. In Part II, the fingertip force-velocity characteristics resulting from the flexible tendon sheath are studied. It indicates that the fingertip force–velocity workspace can be greatly augmented owing to the self-adaptive morphing of the flexible tendon sheaths, showing the average improvement of 41.2% theoretically and 117.5% experimentally compared with the results of 2 mm, 4 mm, and 6 mm size rigid tendon sheaths. Grasping tests and comparisons are then conducted with four three-fingered robotic hands (one with the robotic finger proposed in Part I, one with hinge joints, one with linear extensors, and one with rigid tendon sheaths) and the human hands of six subjects to handle various objects on flat, rough, and soft surfaces. The results show that the novel bio-inspired design in this research could improve the grasping success rates of the robotic hand. Compared with the grasping test results from the robotic hand with the bio-inspired robotic finger proposed in Part I, the overall grasping performance of a robotic hand with hinge joints, linear extensors, and rigid tendon sheaths decreases by 10%, 6%, and 17%, respectively. The results have also shown that with the embedded biomechanical advantages, even without complex control and sensory systems, the robotic fingers can achieve very comparable performance to human fingers in the grasping demonstrations presented, indicating average 94% of the success rate achieved by the human fingers. Successfully demonstrating 14 of 16 grasp types in the Cutkoskey taxonomy further shows the human-finger-like grasping capability of the proposed robotic fingers.