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arXiv · 2108.12358

Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction

Yash Vyas·Mike Allenspach·Christian Lanegger·Roland Siegwart·Marco Tognon
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Abstract

An approach to model and estimate human walking kinematics in real-time for Physical Human-Robot Interaction is presented. The human gait velocity along the forward and vertical direction of motion is modelled according to the Yoyo-model. We designed an Extended Kalman Filter (EKF) algorithm to estimate the frequency, bias and trigonometric state of a biased sinusoidal signal, from which the kinematic parameters of the Yoyo-model can be extracted. Quality and robustness of the estimation are improved by opportune filtering based on heuristics. The approach is successfully evaluated on a real dataset of walking humans, including complex trajectories and changing step frequency over time.

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Yash Vyas, Mike Allenspach, Christian Lanegger, Roland Siegwart, Marco Tognon. 2021-08-27. Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction. https://arxiv.org/abs/2108.12358

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