  This paper presents a novel approach for incremental semiparametric inverse
dynamics learning. In particular, we consider the mixture of two approaches:
Parametric modeling based on rigid body dynamics equations and nonparametric
modeling based on incremental kernel methods, with no prior information on the
mechanical properties of the system. This yields to an incremental
semiparametric approach, leveraging the advantages of both the parametric and
nonparametric models. We validate the proposed technique learning the dynamics
of one arm of the iCub humanoid robot.
