This paper deals with the problem of identifying the inertia parameters of a manipulator. We begin by introducing the terminology of minimal linear combinations (MLC's) of the inertia parameters that are linearly independent of one another and determine the manipulator dynamics while keeping the number of linear combinations of the inertia parameters to a minimum. The problem is then to find an identification procedure for estimating the MLC's and to use the MLC's in the inverse dynamics for control. The recursive Newton-Euler formulation is rederived in terms of the MLC's. The resulting formulation is almost as efficient as the most efficient formulation in the literature. This formulation also provides a starting point from which to derive a recursive identification procedure. The identification procedure is simple and efficient, since it does not require symbolic closed-form equations and it has a recursive structure. The three themes concerning the dynamic modeling of a manipulator $the MLC's, the inverse dynamics in terms of the MLC's, and the identification procedure - are treated in sequence. >
['Shir-Kuan Lin']
Minimal linear combinations of the inertia parameters of a manipulator