This paper proposes a method for modeling and planning the grasping configuration of a robotic hand with underactuated finger mechanisms. The proposed modeling algorithm is based on analysis and mimicking of human grasping experience. Results of the analysis is preprocessed and stored in a database. The grasp configuration planning algorithm can be used within a real time online grasp control as based on artificial neural networks. Namely, shapes and sizes of task objects are described by taxonomy data, which are used to generate grasp configurations. Then, a robot hand grasp control system is designed as based on the proposed grasp planning with close-loop position and force feedback. Simulations and experiments are carried out to show the basic features of the proposed formulation for identifying the grasp configurations while dealing with target objects of different shapes and sizes. It is hoped that the well-trained underactuated robot hand can solve most of grasping tasks in our life. The research approach is aimed to research low-cost easy-operation solution for feasible and practical implementation.

Grasp configuration planning for a low-cost and easy-operation underactuated three-fingered robot hand

Carbone, Giuseppe;
2018

Abstract

This paper proposes a method for modeling and planning the grasping configuration of a robotic hand with underactuated finger mechanisms. The proposed modeling algorithm is based on analysis and mimicking of human grasping experience. Results of the analysis is preprocessed and stored in a database. The grasp configuration planning algorithm can be used within a real time online grasp control as based on artificial neural networks. Namely, shapes and sizes of task objects are described by taxonomy data, which are used to generate grasp configurations. Then, a robot hand grasp control system is designed as based on the proposed grasp planning with close-loop position and force feedback. Simulations and experiments are carried out to show the basic features of the proposed formulation for identifying the grasp configurations while dealing with target objects of different shapes and sizes. It is hoped that the well-trained underactuated robot hand can solve most of grasping tasks in our life. The research approach is aimed to research low-cost easy-operation solution for feasible and practical implementation.
Experimental testing; Grasp configuration planning; Robotic hand; Simulation; Underactuation
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/300906
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