动作接地与非动作接地三维形状特征在物体功能分类中的比较

Barry Ridge, Emre Ugur, A. Ude
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引用次数: 7

摘要

最近在机器人领域的工作,特别是在对象操作和功能学习领域,已经看到了基于动作的特征的发展,也就是说,对象特征是根据操作动作动态定义的。而不是使用姿势不变的特征,就像物体识别的情况一样,这些特征是基于对物体的操作,例如,通过使用描述物体表面相对于推动接触点和方向的形状特征。在本文中,我们提供了一个实验比较的动作接地特征和非接地特征在对象的功能分类设置。通过实验平台收集Kinect RGB-D传感器的3d数据,以及电磁跟踪系统的推动动作轨迹,我们提供的实验结果证明了这种基于行动的方法在一系列最先进的分类器中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of action-grounded and non-action-grounded 3-D shape features for object affordance classification
Recent work in robotics, particularly in the domains of object manipulation and affordance learning, has seen the development of action-grounded features, that is, object features that are defined dynamically with respect to manipulation actions. Rather than using pose-invariant features, as is often the case with object recognition, such features are grounded with respect to the manipulation of the object, for instance, by using shape features that describe the surface of an object relative to the push contact point and direction. In this paper we provide an experimental comparison between action-grounded features and non-grounded features in an object affordance classification setting. Using an experimental platform that gathers 3-D data from the Kinect RGB-D sensor, as well as push action trajectories from an electromagnetic tracking system, we provide experimental results that demonstrate the effectiveness of this action-grounded approach across a range of state-of-the-art classifiers.
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