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Direct Perception of Easily Visible Information for Unknown Object Grasping

机译:对未知物体抓握的易于看见信息的直接感知

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This paper discusses the estimation of the easily visible information for deciding action of unknown object grasping without all of predefined knowledge in a real situation. To estimate the easily visible information, active perception is an important concept. A conventional active perception method estimates an optimum sensing position to measure the accurate object information. However, a robot has to move all around the object to measure the accurate data beforehand. This is not realistic for a robot operation. On the other hand, a robot wants to know the most easily visible sensing position in the neighborhood of a current position to make a decision as soon as possible from a viewpoint of a robot action. As a first step, we propose an estimation of an easily visible information using a point cloud data of an object which is limited data. Now, we apply the unknown object detection method based on plane detection. And, we propose the graspability and the easily visible information estimation method from the point cloud data of the object. We verify the proposed method in a multiple object environment. The effectiveness of our proposal are discussed for grasping an unknown object.
机译:本文讨论了在实际情况下,在没有所有预定义的知识的情况下估计未知物体抓取的易于看见信息。为了估计易于看见的信息,积极的感知是一个重要的概念。传统的有源感知方法估计以测量准确对象信息的最佳感测位置。然而,机器人必须在对象周围移动以预先测量准确的数据。这对机器人操作并不现实。另一方面,机器人希望从机器人动作的观点来看,在当前位置的附近知道最容易的可见感测位置,以便尽快做出决定。作为第一步,我们提出了使用与数据有限的对象的点云数据估计易于看可见的信息。现在,我们应用基于平面检测的未知物体检测方法。并且,我们提出了来自对象的点云数据的避神和易于可见的信息估计方法。我们验证了多个对象环境中的提出方法。讨论了我们提案的有效性,用于抓住一个未知的物体。

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