基于触觉的物体中心的大规模探索和辨别

Kunpeng Yao, Mohsen Kaboli, G. Cheng
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引用次数: 24

摘要

在机器人任务中,可以根据物体的物理性质,如颜色、形状、刚度和表面纹理来实现物体的识别和区分。然而,如果这些外部属性相似甚至相同,则可能失效。在这种情况下,可以考虑物体的内部性质,例如,质心。质心是物体的一种重要的内在物理性质;然而,由于其难以确定,它从未被应用于目标识别任务中。在这项工作中,我们提出了一种基于触觉的方法来探索刚性物体的质心,并将其应用于机器人物体识别任务。该工作包括三个方面:(a)连续估计目标物体的几何信息,(b)探索质心,(c)基于质心特征的目标识别。实验结果表明,采用该方法可以准确地估计实验物体的质心,并能成功地区分具有相同外部性质但质量分布不同的物体。我们的方法对实验对象的纹理特性和刚度也具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tactile-based object center of mass exploration and discrimination
In robotic tasks, object recognition and discrimination can be realized according to their physical properties, such as color, shape, stiffness, and surface textures. However, these external properties may fail if they are similar or even identical. In this case, internal properties of the objects can be considered, for example, the center of mass. Center of mass is an important inherent physical property of objects; however, due to the difficulties in its determination, it has never been applied in object discrimination tasks. In this work, we present a tactile-based approach to explore the center of mass of rigid objects and apply it in robotic object discrimination tasks. This work comprises three aspects: (a) continuous estimation of the target object's geometric information, (b) exploration of the center of mass, and (c) object discrimination based on the center of mass features. Experimental results show that by following our proposed approach, the center of mass of experimental objects can be accurately estimated, and objects of identical external properties but different mass distributions can be successfully discriminated. Our approach is also robust against the textural properties and stiffness of experimental objects.
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