Fuzzy logic expert system for selecting robotic hands using kinematic parameters

Abstract

Industry 4.0 is the current industrial revolution and robotics is an important factor for carrying out high dexterity manipulations. However, mechatronic systems are far from human capabilities and sophisticated robotic hands are highly priced. This paper describes a Fuzzy Logic Expert System (FLES) to map kinematic parameters from robotic hand features to the level of dexterity. The final goal is to obtain the adequate robotic hand that can do ranges of specific tasks according to the level of dexterity required. The FLES uses important kinematic parameters of the human hand/robotic hand: number of fingers, number of Degrees of Freedom (DoF), and number of contacts that grasping involves. As a result, several robotic hands are evaluated using the FLES to determine the type of dexterity task that corresponds to each robotic hand.