Local implicit surface estimation for haptic exploration
Local implicit surface estimation for haptic exploration
复制标题
用于触觉探索的局部隐式表面估计
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
T. Asfour
中科院分区：
文献类型：
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作者：
Simon Ottenhaus;Martin Miller;David Schiebener;N. Vahrenkamp;T. Asfour
自主抓取和操纵未知物体是仿人机器人的核心技能。这是特别具有挑战性的，因为形状信息需要从通常是嘈杂和不完整的感官数据中获得。然而，物体形状信息通常是抓取和操纵规划的关键先决条件，因此即使可用的传感器数据有限，也需要进行估计。我们提出了一种基于稀疏接触信息的隐式表面建模方法，因为它产生于例如触觉探索。使用接触点及其法线局部定义表面，并通过整合此部分信息来外推对象形状。对于有助于估计的每个接触，局部凸性或局部凸度取决于其邻居及其各自的法线。考虑到接触位置，法线和局部凸或凹，整个表面的隐式形状势生成。与基于高斯过程的流行方法相比，这种表示允许边缘和角落等局部细节，而不会在噪声情况下失去插值能力。此外，它还提供了指导迭代探索算法的信息。所提出的方法进行评估，具有平坦和弯曲的表面区域，以及凸和凹的边缘的各种3D形状的集合。
Autonomous grasping and manipulation of unknown objects is a central skill for humanoid robots. This is particularly challenging, as shape information needs to be obtained from sensory data which is often noisy and incomplete. However, object shape information is usually a key prerequisite for grasp and manipulation planning and thus needs to be estimated even if the available sensor data is limited. We propose a method for implicit surface modeling based on sparse contact information, as it arises e.g. from haptic exploration. Surfaces are locally defined using the contact points and their normals, and the object shape is extrapolated by integrating this partial information. For each contact contributing to the estimation, the local convexity or concavity is determined depending on its neighbors and their respective normals. Taking into account contact positions, normals and local convexities or concavities, the Implicit Shape Potential of the overall surface is generated. In contrast to popular methods based on Gaussian Processes, this representation allows for local details like edges and corners, without losing the ability to interpolate in the case of noise. In addition, it provides information to guide iterative exploration algorithms. The proposed method is evaluated on a set of various 3D shapes that possess flat and curved surface regions as well as convex and concave edges.