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Efficient shape and pose recovery of unknown objects from three camera views

机译:高效的形状和从三个相机视图中的未知对象的恢复

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Knowing the shape and pose of objects of interest is critical information when planning robotic grasping and manipulation maneuvers. The ability to recover this information from objects for which there is no a priori knowledge is a valuable behavior for an autonomous or semi-autonomous robot. In this paper, we present methods and algorithms for the shape and pose recovery of unknown objects using no a priori information. Three camera views are taken of the object from three mutually orthogonal directions. Using shape from silhouettes, a point surface reconstruction of the object is performed and a superquadric is fit to the resulting array of points. We show through simulation and experiment that this method yields reconstruction accuracy sufficient for planning and executing grasping maneuvers. In addition to novel contributions, we have made performance improvements to recently published algorithms.
机译:知道感兴趣对象的形状和姿势是规划机器人抓握和操纵机构时的关键信息。 从没有先验知识的对象中恢复这些信息的能力是自主或半自治机器人的宝贵行为。 在本文中,我们使用不先验信息呈现用于形状的方法和算法并占据未知对象的恢复。 从三个相互正交的方向拍摄对象的三个相机视图。 使用来自轮廓的形状,执行对象的点表面重建,并且超级摩擦力适合得到的点阵列。 我们通过仿真和实验展示了这种方法产生的重建精度,足以规划和执行抓握机动。 除了新颖的贡献之外,我们还对最近发表的算法进行了绩效改进。

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