Literature DB >> 33501063

An Adaptive Actuation Mechanism for Anthropomorphic Robot Hands.

George P Kontoudis1, Minas Liarokapis2, Kyriakos G Vamvoudakis3, Tomonari Furukawa1.   

Abstract

This paper presents an adaptive actuation mechanism that can be employed for the development of anthropomorphic, dexterous robot hands. The tendon-driven actuation mechanism achieves both flexion/extension and adduction/abduction on the finger's metacarpophalangeal joint using two actuators. Moment arm pulleys are employed to drive the tendon laterally and achieve a simultaneous execution of abduction and flexion motion. Particular emphasis has been given to the modeling and analysis of the actuation mechanism. More specifically, the analysis determines specific values for the design parameters for desired abduction angles. Also, a model for spatial motion is provided that relates the actuation modes with the finger motions. A static balance analysis is performed for the computation of the tendon force at each joint. A model is employed for the computation of the stiffness of the rotational flexure joints. The proposed mechanism has been designed and fabricated with the hybrid deposition manufacturing technique. The efficiency of the mechanism has been validated with experiments that include the assessment of the role of friction, the computation of the reachable workspace, the assessment of the force exertion capabilities, the demonstration of the feasible motions, and the evaluation of the grasping and manipulation capabilities. An anthropomorphic robot hand equipped with the proposed actuation mechanism was also fabricated to evaluate its performance. The proposed mechanism facilitates the collaboration of actuators to increase the exerted forces, improving hand dexterity and allowing the execution of dexterous manipulation tasks.
Copyright © 2019 Kontoudis, Liarokapis, Vamvoudakis and Furukawa.

Entities:  

Keywords:  bioinspiration; robot hands; robotic fingers; tendon-driven mechanisms; underactuation

Year:  2019        PMID: 33501063      PMCID: PMC7805973          DOI: 10.3389/frobt.2019.00047

Source DB:  PubMed          Journal:  Front Robot AI        ISSN: 2296-9144


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