Identification of dynamics of humanoids: Systematic exciting motion generation

Abstract

The mass parameters of robots influence performances of model-based control and validation of the simulation results. The mass parameters provided by CAD data are usually rough approximation of the true parameters. Therefore several methods for estimation of those parameters have been proposed. Their precision depends on the used motion, called optimal exciting trajectories. This paper describes a new approach to determine humanoid robot exciting trajectories for mass parameters identification. The method was inspired by the studies done in the field of human mass parameters identification, and it is based on observation of condition numbers of sub-regressor matrices created from the columns of the regressor matrix. The method has been experimentally applied to identify mass parameters of HRP-2 and HRP-4 humanoid robots. The proposed method is able to reconstruct ground reaction forces and force moments more accurately than parameters obtained from CAD data.