Adaptive Teleoperation Control using Online Estimate of Operator's Arm Damping

Indirect adaptive bilateral teleoperation controllers have been designed to provide compromise between stability and performance in the presence of time delays and uncertainties in operator and environment dynamics. So far, the controllers developed utilize online estimate of only environment impedance and they approximate the operator's arm highly time-varying dynamics with linear-time-invariant dynamic models. In this paper, a force-position teleoperation controller is implemented in which the master damping is adjusted in a dual manner based on the online estimate of operator's arm damping. To this purpose, a novel methodology for online estimation of forearm damping when arm movement is restricted to only elbow joint motion in horizontal plane is developed. The proposed scheme uses elbow joint angular position and velocity, and electromyogram signals collected from upper arm muscles in a radial basis function artificial neural network for online estimation of damping parameter. The adaptive bilateral controller has experimentally demonstrated superior performance and contact stability compared to a conventional force-position controller in the presence of communication delays