Neuro-Fuzzy Grasp Control for a Teleoperated Five Finger Anthropomorphic Robotic Hand
Author | : Maxwell Joseph Welyhorsky |
Publisher | : |
Total Pages | : |
Release | : 2021 |
ISBN-10 | : OCLC:1294013199 |
ISBN-13 | : |
Rating | : 4/5 (99 Downloads) |
Book excerpt: Robots should offer a human-like level of dexterity when handling objects if humans are to be replaced in dangerous and uncertain working environments. This level of dexterity for human-like manipulation must come from both the hardware, and the control. Exact replication of human-like degrees of freedom in mobility for anthropomorphic robotic hands are seen in bulky, costly, fully actuated solutions, while machine learning to apply some level of human-like dexterity in underacted solutions is unable to be applied to a various array of objects. This thesis presents experimental and theoretical contributions of a novel neuro-fuzzy control method for dextrous human grasping based on grasp synergies using a Human Computer Interface glove and upgraded haptic-enabled anthropomorphic Ring Ada dexterous robotic hand. Experimental results proved the efficiency of the proposed Adaptive Neuro-Fuzzy Inference Systems to grasp objects with high levels of accuracy.