増分セミパラメトリック逆動力学学習
Incremental Semiparametric Inverse Dynamics Learning
剛体力学に基づくパラメトリックモデルと増分カーネル法によるノンパラメトリックモデルを組み合わせ、iCubヒューマノイドの腕の逆動力学をオンライン学習する手法を提案した。
著者: Raffaello Camoriano, Silvio Traversaro, Lorenzo Rosasco, Giorgio Metta, Francesco Nori
分類: stat.ML, cs.LG, cs.RO
原文アブストラクト
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.
