A New Method for Online Parameter Estimation of Hunt-Crossley Environment Dynamic Models

Abstract

Online estimates of unknown environment dynamics are used for the control of robotic contact tasks. The Hunt-Crossley nonlinear dynamic model of environments has been shown to be more consistent with the physics of contact, compared to the classical linear models, such as Kelvin-Voigt. This paper proposes a new method for online parameter estimation of Hunt-Crossley model and provides a mild set of conditions for guaranteed unbiased estimation. The rate and the sensitivity of convergence to parameter initialization and system parameter changes are numerically evaluated and compared for both the proposed method and an existing 2-stage identification method.