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相关概念视频

Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

478
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
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相关实验视频

Updated: Sep 16, 2025

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
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为大规模虚拟环境规范以任务为导向的人机交互.

Burak Balta, Khandaker Nusaiba Hafiz, Jonathan Realmuto

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    |July 11, 2025
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    概括
    此摘要是机器生成的。

    这项研究通过调整机器人的虚拟刚性来标准化用户在身体康复任务中的努力. 全尺度缩放最大限度地减少了不同物理属性的用户之间的努力差异.

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    相关实验视频

    Last Updated: Sep 16, 2025

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    科学领域:

    • 机器人技术 机器人技术 机器人技术
    • 人与计算机的交互
    • 生物力学 生物力学

    背景情况:

    • 物理模拟平台 (haptic manipulanda,机器人康复系统) 便于控制的人机交互.
    • 用户的物理属性 (例如身高,质量) 的个体差异引入了任务一致性和努力的变化.
    • 标准化用户努力对于康复,运动学习和人机协作研究中的可靠数据至关重要.

    研究的目的:

    • 开发和验证一种方法来标准化使用机器人操纵器执行的物理跟踪任务中的用户努力.
    • 为了研究机器人虚拟刚度缩放对用户努力一致性的影响.
    • 确定虚拟刚性的最佳缩放因子,以最大限度地减少具有不同物理特征的用户之间的努力差异.

    主要方法:

    • 使用机器人操纵器模拟了一个物理跟踪任务.
    • 该研究分析了缩放因子对机器人的虚拟刚度矩阵的影响,这是一个关键阻抗参数.
    • 模拟使用9个虚拟参与者进行,他们的身高和体重各不相同.

    主要成果:

    • 通过 (质量/高度) ^ 2 / 3的因子对机器人的虚拟刚度进行全米缩放被发现是最有效的方法.
    • 这种扩展方法显著降低了具有不同物理属性的虚拟参与者之间的努力差异.
    • 这些发现展示了一种可量化的方法,可以将机器人行为适应个人用户特征.

    结论:

    • 拟议的全米缩放方法促进了自适应物理模拟平台的开发.
    • 这种方法提高了在康复和研究环境中人机交互的一致性和可靠性.
    • 这些发现对个性化康复,运动学习研究和人机协作有影响.