Recent developments on modeling for a 3-DOF micro-hand based on AI methods

Abstract

Recently, soft actuators have been expected to have many applications in various fields. Most of the actuators are composed of flexible materials and driven by air pressure. The 3-DOF micro-hand, which is a kind of soft actuator, can realize a three degrees of freedom motion by changing the applied air pressure pattern. However, the input-output relation is nonlinear and complicated. In previous research, a model of the micro-hand was proposed, but an error between the model and the experimental results was large. In this paper, modeling for the micro-hand is proposed by using multi-output support vector regression (MSVR) and ant colony optimization (ACO), which is one of the artificial intelligence (AI) methods. MSVR estimates the input-output relation of the micro-hand. ACO optimizes the parameters of the MSVR model.