Bi-manual robotic paper manipulation based on real-time marker tracking and physical modelling
Bi-manual robotic paper manipulation based on real-time marker tracking and physical modelling
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DOI：
10.1109/iros.2011.6094742
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发表时间：
2011-12
期刊：
影响因子：
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通讯作者：
Christof Elbrechter;R. Haschke;H. Ritter
中科院分区：
文献类型：
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作者：
Christof Elbrechter;R. Haschke;H. Ritter
操纵可变形物体（如纺织品或纸张）的能力，是使铰接机械手的能力更接近人类人工智能水平的一个主要先决条件。我们专注于纸的操作，这为我们提供了一个丰富的交互领域，这是拟人机器人手尚未解决的问题。为此需要的关键能力是在遮挡和强变形条件下对纸张进行鲁棒跟踪和建模。我们提出了一个基于标记的框架，可以鲁棒地实时实现这些特性。我们将纸张流形的纯数学表示与软体物理模型进行了比较，并演示了使用我们的视觉跟踪方法来促进两只拟人化的20 DOF阴影灵巧手在抓住一张平放的纸时的协调，使用视觉引导的膨胀和挤压组合。
The ability to manipulate deformable objects, such as textiles or paper, is a major prerequisite to bringing the capabilities of articulated robot hands closer to the level of manual intelligence exhibited by humans. We concentrate on the manipulation of paper, which affords us a rich interaction domain and that has not yet been solved for anthropomorphic robot hands. A key ability needed for this is the robust tracking and modelling of paper under conditions of occlusion and strong deformation. We present a marker based framework that realizes these properties robustly and in real-time. We compare a purely mathematical representation of the paper manifold with a soft-body-physics model and demonstrate the use of our visual tracking method to facilitate the coordination of two anthropomorphic 20 DOF Shadow Dexterous Hands while they grasp a flat-lying piece of paper, using a combination of visually guided bulging and pinching.