A solution method for predictive simulations in a stochastic environment

JOURNAL OF BIOMECHANICS

卷:104

Article

Koelewijn, Anne D.^1,2,3  van den Bogert, Antonie J.¹ 

[1] Cleveland State Univ, Dept Mech Engn, Cleveland, OH 44115 USA

[2] Ecole Polytech Fed Lausanne, Biorobot Lab, Inst Bioengn, Lausanne, Switzerland

[3] Friedrich Alexander Univ Erlangen Nurnberg, Fac Engn, Machine Learning & Data Analyt Lab, Erlangen, Germany

关键词: Predictive simulations;    Uncertainty;    Trajectory optimizations;   

DOI  :  10.1016/j.jbiomech.2020.109759

来源: Elsevier

【 摘 要 】

Predictive gait simulations currently do not account for environmental or internal noise. We describe a method to solve predictive simulations of human movements in a stochastic environment using a collocation method. The optimization is performed over multiple noisy episodes of the trajectory, instead of a single episode in a deterministic environment. Each episode used the same control parameters. The method was verified on a torque-driven pendulum swing-up problem. A different optimal trajectory was found in a stochastic environment than in the deterministic environment. Next, it was applied to gait to show its application in predictive simulation of human movement. We show that, unlike in a deterministic model, a nonzero minimum foot clearance during swing is predicted by a minimum-effort criterion in a stochastic environment. The predicted amount of foot clearance increased with the noise amplitude. (C) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free