Detection and evaluation of grasping positions
Detection and evaluation of grasping positions
复制标题
抓取位置的检测和评估
DOI：
10.1145/1187112.1187207
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
M. Nakajima
中科院分区：
文献类型：
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作者：
Fumihito Kyota;Tomoyuki Watabe;S. Saito;M. Nakajima
对于在虚拟世界中自主进化的类人智能体来说，抓取物体的动作是非常重要的。当一个智能体被命令“抓取物体”时，它必须确定要抓取物体的哪一部分。因此，有必要识别三维几何形状的形式，并检测哪些部分适合于抓握。然而，选择并不容易，因为对于一个对象有很多可能的抓取方法。我们用两种方法来解决这个问题。一个是使用神经网络来找到一个合适的手的形状，给定一个特定的形状来抓住。第二个是计算机器人抓取稳定性的技术。在这个草图中，我们的主要贡献如下：1）检测物体表面上的适当部分，假设物体由一只手抓取; 2）形成手的形状来抓取各种形状的物体。使用这两种方法，计算抓取位置和手的形状，为他们每个人成为可能。
The action of grasping an object is very important for a humanoid agent with hand, evolving autonomously in a virtual world. When an agent is ordered “Grasp the object”, it has to determine which portion of the object to grasp. Therefore, it is necessary to recognize the form of the 3-dimensional geometry, and detect which portions are suitable to grasp. However, the selection is not easy because there are a lot of possible grasping methods for one object. We solve this point by two methods. One uses a neural network to find a suitable shape of the hand given a certain shape to grasp. The second is a technique to calculate the stability of grasping in robotics.In this sketch, our main contributions are as follows: 1) detecting the appropriate portions to be grasped on the surface of an object, assuming that the object is grasped by one hand; 2) formation of the hand shape to grasp various shaped objects. Using two proposed methods, computing grasping positions and hand shapes for each of them becomes possible.