Neuro-fuzzy control of a biped robot able to be subjected to an external pushing force in the sagittal plane

Abstract

This paper describes the control of an autonomous biped robot capable to be subjected to external pushing forces applied in the sagittal plane. A 1st order Takagi-Sugeno-Kang (TSK) type neuro fuzzy net, that was trained based on experimental and simulation data, is used. This net uses the zero moment point (ZMP) position and its variation as inputs, and the sagittal correction of the robotpsilas body is obtained as the output. The ZMP is obtained be acquiring use of the force distribution on four force sensors placed under each robotpsilas foot. The gait implemented on our biped is similar to a human gait. A human gait was acquired and adapted to the robot size. Some experiments were carried out and the results show that the used gait combined with the TSK neuro fuzzy net is appropriate to be used in the control of a biped robot, with and without an applied external force.