物理的人間-ロボット相互作用のための歩行運動のモデリングと推定
Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction
ヨーヨーモデルに基づき人間の歩行速度をモデル化し、拡張カルマンフィルタで周波数・バイアス・正弦波状態を推定して歩行キネマティクスをリアルタイム推定する手法を提案した。
著者: Yash Vyas, Mike Allenspach, Christian Lanegger, Roland Siegwart, Marco Tognon
分類: cs.RO
原文アブストラクト
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.
