Terrain classification and locomotion parameters adaptation for humanoid robots using force/torque sensing

Abstract

This paper describes a terrain classification method based on the readings from the force/torque sensors mounted on the ankles of a humanoid robot. The experimental results on five different terrain types, showed very high precision and recall identification rates, i.e. 95%, that are surpassing the state-of-the-art ones for quadrupeds and hexapods. Based on the acquired data during a set of walking experiments, we evaluated the stability of locomotion on all of the terrains. We also present a method to find an optimal step size, which optimises both the energy consumption and the stability of locomotion, given the identified terrain type. For the experimental data collection we used the full-size humanoid robot WALK-MAN walking on five different types of terrain.