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New method for decoupling the articular stiffness identification: Application to an industrial robot with double encoding system on its 3 first axis

机译:解耦关节刚度识别的新方法:在工业机器人的第三个3轴上采用双编码系统的应用

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In order to be able to perform complex and arduous tasks, stiffness articular identification of industrial robots is a current approach to predict the deflection under static or dynamic loading. Manufacturers propose new features to take the loading into account and a new generation of industrial robot equiped with double encoding systems are proposed. However, current methods brings some drawbacks when the ratio between the stiffness arm and the wrist one is too high. In this paper, we propose a new approach to take this aspect into account by decoupling the arm identification and the wrist one. We compare then our method regarding two current methods and applied it on this new industrial robot. The results highlight the stability and the quality of the stiffness articular estimation with and without activating the double encoding system. On our data, we are able to take into account 84% of the global deflection.
机译:为了能够执行复杂而艰巨的任务,工业机器人的刚度关节识别是目前预测静态或动态载荷下挠度的一种方法。制造商提出了考虑到负载的新功能,并提出了配备双编码系统的新一代工业机器人。然而,当刚度臂和腕部之间的比率太高时,当前的方法带来一些缺点。在本文中,我们提出了一种新方法,通过将手臂识别和手腕识别分开来考虑这一方面。然后,我们将我们的方法与当前的两种方法进行比较,并将其应用于这种新型工业机器人。结果突出显示了在激活和未激活双重编码系统的情况下,刚度关节估计的稳定性和质量。根据我们的数据,我们能够考虑到全球挠度的84%。

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