Industrial Robot Parameter Identification using a Constrained Instrumental Variable Method

Abstract

Robot identification is a prolific topic that has a long history with results spanning recent decades. Recent years have witnessed a renew of interest in this problem due in part to a rapid increase in robotic hardware platforms capable of accurate model-based control. The most popular methods exploit the fact that the inverse dynamic model is linear to the dynamic parameters. Because we identify robots with closed-loop procedures, an Instrumental Variable approach called IDIM-IV (Inverse Dynamic Identification Model with Instrumental Variable estimation) that combines the direct and inverse dynamic models to prevent from correlation between errors has been successfully validated. However, IDIM-IV does not guarantee that the direct dynamic model will be well-posed during its iterations because of possible modeling errors. In this paper, we combine physical constraints and IDIM-IV to address this deficiency for IDIM-IV. This new constrained IV approach, called PC-IDIM-IV (Physically Consistent IDIM-IV), consists of two nested iterative algorithms: an outer one that is IDIM-IV and an inner one that accounts for the physical constraints solved by a Gauss-Newton algorithm. Experimental results and comparisons with other methods carried out with the TX40 robot show the feasibility of PC-IDIM-IV.