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人类在障碍物上的移动揭示了能耗的实时预测,以优化决策
Katherine A J Daniels1,2,3, J F Burn2
1Department of Sport and Exercise Sciences, Manchester Metropolitan University, Manchester M1 7EL, UK.
Proceedings. Biological sciences
|June 14, 2023
概括
人类通过事先选择障碍物谈判策略来优化机动能源成本. 视觉可以选择最节能的路径,即使没有直接的感官反,也可以显示出预测控制.
科学领域:
- 生物力学 生物力学
- 人类的机动运动
- 机器人技术 机器人技术 机器人技术
- 神经科学是一个神经科学.
背景情况:
- 动物最大限度地降低了运动能量成本,但这如何塑造复杂地形上的步态尚不清楚.
- 对于复杂的,多步骤的任务,人类运动优化原理尚未完全被理解.
- 在机车运动中预测控制和决策需要进一步调查.
研究的目的:
- 研究能源消耗在复杂地形上适应步态选择中的作用.
- 为了确定人类是否提前选择能效最佳的机动运动策略.
- 探索视觉和遥感对节能机动的影响.
主要方法:
- 参与者执行了一项强制选择任务,涉及多步骤的障碍谈判 (穿越"洞").
- 对各种策略和障碍尺寸进行了运输机械能源成本建模和分析.
- 基于视觉的遥感被用来评估预期的战略选择.
主要成果:
- 机车战略选择的准确预测是整个任务的综合相对能源成本.
- 在遇到障碍之前,参与者选择了具有最低预期能源成本的战略.
- 仅仅视觉就足以选择最节能的策略,而不依赖于在线反.
结论:
- 人类在复杂地形上的移动通过提前决策来优化能源效率.
- 使用遥感,突出预测控制,可以进行步态的精力优化.
- 为运动控制研究提出了一个行为框架,将力学,遥感和认知联系起来.
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