A robotic bipedal model for human walking with slips

Abstract

Slip is the major cause of falls in human locomotion. We present a new bipedal modeling approach to capture and predict human walking locomotion with slips. Compared with the existing bipedal models, the proposed slip walking model includes the human foot rolling effects, the existence of the double-stance gait and active ankle joints. One of the major developments is the relaxation of the nonslip assumption that is used in the existing bipedal models. We conduct extensive experiments to optimize the gait profile parameters and to validate the proposed walking model with slips. The experimental results demonstrate that the model successfully predicts the human recovery gaits with slips.