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Facilitating Robotic Subtask Reuse by a New Representation of Parametrized Solutions

机译:通过参数化解决方案的新代表促进机器人子任务重用

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In this paper, we suggest a coherent way of representing results from experiments associated with robotic assembly. The purpose of the representation is to be able to reuse the experiments in other assembly settings. A main novelty in our representation is the inclusion of fine grained experimental uncertainties such as e.g. deviations between a sensed object pose and the actual pose, and we discuss why it is very important for the reusability of experiments to include these uncertainties. Under the reasonable assumption that we can represent the uncertainties as a region around the origin in a potentially high dimensional Cartesian space, we show that we can efficiently represent the studied deviations by storing experiments on a so called spherical lattice. We illustrate that the representation works by studying simulation experiments on two different industrial use cases involving grasping an object and mounting an object on a fixture.
机译:在本文中,我们建议代表与机器人组件相关的实验结果的相干方式。表示的目的是能够在其他装配设置中重用实验。我们代表中的主要新颖性是包含细粒度的实验性不确定性,例如例如,感觉物体姿势和实际姿势之间的偏差,我们讨论了为什么对包括这些不确定性的实验的可重用性非常重要。在合理的假设下,我们可以将不确定性作为潜在的高维笛卡尔空间中的原点周围的区域代表,我们表明我们可以通过在所谓的球形格子上存储实验来有效地代表研究的偏差。我们说明了代表性通过研究两种不同工业用例的模拟实验,涉及抓住物体并在夹具上安装物体。

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