摘要
由一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-机器人的新研究是一份报告的主旨。根据NewsRx编辑S在意大利热那亚的新闻报道，研究表明，“神经生理学研究表明，人类能够适应手部的机械硬度，以抵御干扰。他的研究启发了在按摩任务中优化机器人手臂的硬度。”这项研究的财政支持来自国家援助研究所。我们的新闻记者从意大利技术学院的研究中引用了一句话：“端点刚度是在笛卡尔空间中建模的，”就好像手是一个独立的刚体，但是手臂是一系列通过关节连接的刚体，关节和手臂结构对端点刚度的贡献还没有被量化。本文采用数学优化方法，找出了在外力作用下最大刚度和完整度的条件。通过这样做，我们可以追溯地解释使用这些数学最优条件对人类进行的观察。然后，我们展示了如何将这种优化应用于机器人任务规划和控制。在仿人机器人上进行的实验显示，手臂姿态与在人类身上观察到的相似。这表明，人类优化僵硬有一个潜在的物理原理。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news reporting out of Genoa, Italy, by NewsRx editor s, research stated, “Research in neurophysiology has shown that humans are able to adapt the mechanical stiffness at the hand in order to resist disturbances. T his has served as inspiration for optimising stiffness in robot arms during mani pulation tasks.” Financial support for this research came from Istituto Nazionale per l’Assicuraz ione Contro Gli Infortuni sul Lavoro. Our news journalists obtained a quote from the research from the Italian Institu te of Technology, “Endpoint stiffness is modelled in Cartesian space, as though the hand were in independent rigid body. But an arm is a series of rigid bodies connected by articulated joints. The contribution of the joints and arm configur ation to the endpoint stiffness has not yet been quantified. In this paper we us e mathematical optimisation to find conditions for maximum stiffness and complia nce with respect to an externally applied force. By doing so, we can retroactive ly explain observations made about humans using these mathematically optimal con ditions. We then show how this optimisation can be applied to robotic task plann ing and control. Experiments on a humanoid robot show similar arm posture to tha t observed in humans. This suggests there is an underlying physical principle by which humans optimise stiffness.”
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