Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions

Authors:
Chenguang Yang;Gowrishankar Ganesh;Sami Haddadin;Sven Parusel;Alin Albu-Schaeffer;Etienne Burdet
Affiliations:
Department of Bioengineering, Imperial College London, London, U.K.;Department of Bioengineering, Imperial College London, London, U.K.;German Aerospace Center, Wessling, Germany;German Aerospace Center, Wessling, Germany;German Aerospace Center, Wessling, Germany;Department of Bioengineering , Imperial College London, London, U.K.
Venue:
IEEE Transactions on Robotics
Year:
2011

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Abstract

This paper presents a novel human-like learning controller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, without requiring interaction force sensing.