Caging complex objects with geodesic balls
Caging complex objects with geodesic balls
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DOI：
10.1109/iros.2013.6696781
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
D. Zarubin;Florian T. Pokorny;Marc Toussaint;D. Kragic
中科院分区：
文献类型：
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作者：
D. Zarubin;Florian T. Pokorny;Marc Toussaint;D. Kragic
本文提出了一种新的方法来合成物体的抓取，这些物体的几何形状只能在存在噪音的情况下观察。我们特别关注的问题，产生笼把握与现实的机器人手模拟，并表明我们的方法可以产生这样的把握，即使在复杂的物体。我们介绍的想法，使用测地球上的物体的表面，以近似的最大接触面之间的机器人手和物体。我们定义了两种类型的histologics提取近似测地球的信息，以确定一个对象上的区域，可能会被用来生成一个笼子的把握。我们的评分基于两个评分函数。第一个使用缠绕角度测量表面上的测地线球围绕主轴缠绕的程度，而第二个探索使用测地线球的总离散高斯曲率来对潜在的笼状姿势进行排名。我们评估我们的方法相对于手运动学的变化，选择复杂的现实世界中的对象，并就其对噪声的鲁棒性。
This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.