Modelling and control of anthropomorphic fingers for intelligent systems

摘要

In this paper, we present the design of an anthropomorphic finger prototype. The main goal pursued during the development of the finger has been that of designing a small and lightweight dextrous gripper with anthropomorphic kinematics, which could be easily ported and installed even on small robot hands. In this artificial finger, the actuators are Electric Pistons, whose main component is a shape memory alloy (SMA) spring. In addition, a novel technique for SMA drive is implemented. The paper outlines the kinematic and structural characteristics of the finger. We propose to use a physical anthropomorphic finger to demonstrate and validate a neural controller based on biological models. The artificial finger and biological neural control algorithm can be used for modelling the skeleto-motor-control system for the biological motor control community. The neural controller is applied for the coordination of the artificial finger joints. The neural controller applies a strategy of trajectory control using the Vector Integration To Endpoint (VITE) model, which exhibits key kinematic properties of human movements, including asymmetric bell-shaped velocity profiles. The neural controller is an intelligent system that allows to compute the desired joint movement trajectories by smoothly interpolating between initial and final muscle length commands for the antagonist muscles involved in the movement. The rate of interpolation is controlled by the product of a difference vector which continuously computes the difference between the desired and present position of the finger, and a volitional movement gating signal (GO). Experimental performance results in the time domain are presented, and directions for future research are discussed.