A solution method for predictive simulations in a stochastic environment
A solution method for predictive simulations in a stochastic environment
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DOI：
10.1016/j.jbiomech.2020.109759
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发表时间：
2020-05-07
影响因子：
2.4
通讯作者：
van den Bogert, Antonie J.
中科院分区：
文献类型：
--
作者：
Koelewijn, Anne D.;van den Bogert, Antonie J.
预测步态模拟目前没有考虑环境或内部噪声。我们描述了一种方法来解决在随机环境中使用搭配方法的人类运动的预测模拟。优化是在多个有噪声的轨迹片段上进行的，而不是在确定性环境中的单个片段。每一集使用相同的控制参数。通过一个力矩驱动摆摆问题对该方法进行了验证。随机环境下的最优轨迹与确定性环境下的最优轨迹不同。然后，将其应用于步态，展示其在人体运动预测仿真中的应用。我们表明，与确定性模型不同，在随机环境中，通过最小努力标准预测摆动期间的非零最小脚间隙。预测的足部间隙量随着噪声幅值的增大而增大。(C) 2020 Elsevier Ltd.版权所有。
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.