Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction
| Author | |
| 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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| Year of Publication |
2021
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| Conference Name |
2021 Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)
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| Date Published |
2021/10
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