Material classification based on thermal properties — A robot and human evaluation

E. Kerr, T. Mcginnity, S. Coleman
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引用次数: 24

Abstract

The surface properties of an object and the environment in which it is located are important for robot grasping and manipulation. Physical contact with an object using tactile sensors can enable the retrieval of detailed information about the object, i.e. compressibility, surface texture and thermal properties. This paper describes a system that classifies materials based on their thermal properties alone, minimising the amount of manipulation required. Following acquisition of data from a sophisticated tactile sensor, the system uses an Artificial Neural Network (ANN) to classify materials based on representations of their thermal properties. The system was compared with human performance in the task of classifying materials and was found to perform better.
基于热性能的材料分类。机器人和人的评价
物体的表面特性及其所处的环境对机器人的抓取和操作非常重要。使用触觉传感器与物体进行物理接触,可以检索物体的详细信息,即压缩性、表面纹理和热性能。本文描述了一个系统,该系统仅根据材料的热性能对材料进行分类,从而最大限度地减少了所需的操作量。在从复杂的触觉传感器获取数据后,该系统使用人工神经网络(ANN)根据材料的热性能表征对材料进行分类。将该系统与人类在材料分类任务中的表现进行了比较,发现其表现更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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