Position-based impedance control using fuzzy environment models

Impedance control is one of the most effective force control methods for a robot manipulator in contact with an object. It should be noted, however, that a practical study on such a method has not been successfully applied to an industrial robot with 6 degree-of-freedom. A hybrid compliance/force control (HCC) in this field was suggested to deal with the practical problem, in which a desired damping coefficient is determined by repeating many simulations. To determine a suitable compliance without trial and error, we have already presented a tuning method which produces the desired time-varying compliance, giving the critical damping in contact with an object, by using the information on the inertia and Jacobian matrices. But the tuning method needs to measure the physical information of the environment. In this paper, to overcome the problem we propose a fuzzy environment model that can estimate each directional stiffness of the environments. The fuzzy environment model is composed of several fuzzy rules which are learned with genetic algorithms. Simulation results show that the proposed method is very effective for deciding the desired compliance without any complicated tuning and is very robust to the change of environment