Incremental Semiparametric Inverse Dynamics Learning
This addresses incremental learning of robot dynamics without prior mechanical knowledge, but it is incremental/hybrid in nature.
The paper tackles the problem of learning inverse dynamics for robotic arms by combining parametric rigid body dynamics with nonparametric kernel methods, resulting in an incremental semiparametric approach validated on the iCub humanoid robot arm.
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.