Impedance Control Using Anisotropic Fuzzy Environment Models

Abstract

We describe impedance control for force control in unknown environments, proposing anisotropic fuzzy environment models that estimate environmental stiffness using fuzzy reasoning and generate time-varying damping for stable force control. Each model is automatically taught with genetic algorithms (GAs), in which evaluation is made for force control in several known environments. Taught models are integrated for generalization. We apply models to tasks in which an industrial robot sands or polishes wood is differently stiff in different direction. Numerical simulations demonstrate the effectiveness of our method.