Optimized Fuzzy Impedance Control for Empowering Human in Execution of Onerous Task with Manipulators

The proposed contribution describes a fuzzy impedance control based approach to assist the human operator in industrial applications while executing onerous tasks. The developed method allows to set in real-time the set-point of the impedance control on the basis of the humans intentions. Moreover, an off-line optimization of the fuzzy impedance con- trol parameters has been performed through an optimization algorithm based on a neural network approach. The proposed method has been verified in an experimental procedure with 20 human subjects interacting with the manipulator (KUKA iiwa 14 R820). The proposed algorithm has been also validated in an industrial task, performing the installation of a heavy and bulky hatrack component, case-study related to the H2020 CleanSky 2 EURECA project at the KUKA Innovation Award 2017.