Identification of Fully Physical Consistent Inertial Parameters using Optimization on Manifolds
This work addresses the need for accurate inertial parameter identification in robotics, particularly for humanoid robots, and is incremental as it builds on existing methods by adding a previously ignored constraint.
The paper tackled the problem of ensuring inertial parameters correspond to a physical rigid body by introducing a new condition for full physical consistency, which includes both positive definiteness and triangular inequality constraints, and validated it with experiments on the iCub humanoid robot.
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.