Identification of Fully Physical Consistent Inertial Parameters using Optimization on Manifolds

TL;DR

This paper introduces a new condition and parametrization for inertial parameters that guarantees physical consistency, reformulating the identification as a manifold optimization problem validated on a humanoid robot.

Contribution

It proposes a novel fully physical consistency condition and a natural parametrization, enabling inertial parameter identification via manifold optimization ensuring physical realizability.

Findings

The method guarantees positive definiteness and triangular inequality of inertia matrices.

Experimental validation on iCub robot demonstrates effectiveness.

The approach outperforms existing techniques ignoring the triangular inequality.

Abstract

This paper presents a new condition, the fully physical consistency for a set of inertial parameters to determine if they can be generated by a physical rigid body. The proposed condition ensure both the positive definiteness and the triangular inequality of 3D inertia matrices as opposed to existing techniques in which the triangular inequality constraint is ignored. This paper presents also a new parametrization that naturally ensures that the inertial parameters are fully physical consistency. The proposed parametrization is exploited to reformulate the inertial identification problem as a manifold optimization problem, that ensures that the identified parameters can always be generated by a physical body. The proposed optimization problem has been validated with a set of experiments on the iCub humanoid robot.