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This paper presents an algorithm to geometrically characterize inertialparameter identifiability for an articulated robot. The geometric approachtests identifiability across the infinite space of configurations using only afinite set of conditions and without approximation. It can be applied togeneral open-chain kinematic trees ranging from industrial manipulators tolegged robots, and it is the first solution for this broad set of systems thatis provably correct. The high-level operation of the algorithm is based on akey observation: Undetectable changes in inertial parameters can be representedas sequences of inertial transfers across the joints. Drawing on theexponential parameterization of rigid-body kinematics, undetectable inertialtransfers are analyzed in terms of observability from linear systems theory.This analysis can be applied recursively, and lends an overall complexity of$O(N)$ to characterize parameter identifiability for a system of $N$ bodies.Matlab source code for the new algorithm is provided.

A Geometric Characterization of Observability in Inertial Parameter Identification