2 research outputs found

    A robotic bipedal model for human walking with slips

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    Abstract—Slip is the major cause of falls in human locomo-tion. 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 non-slip assumption that is used in the existing bipedal models. We conduct extensive experiments to optimize the model parameters and to validate the proposed walking model with slips. The experimental results demonstrate that the model successfully predicts the human walking and recovery gaits with slips. I

    Pose estimation in physical human-machine interactions with application to bicycle riding

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