Analysis of surface strength in frequency domain using fore-aft distance information of wheeled robots on rough terrain

Jayoung Kim, Jihong Lee
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Abstract

This paper explores a possibility of identifying material types using fore-aft distance information of an ultrasonic sensor which is changed depending on surface strength. Fore-aft distance data are transformed into frequency domain using FFT and frequency data are analyzed for extracting features of a material type. Sensor data are acquired by a testbed for analysis of a wheel-terrain interaction on four types of a surface; asphalt, sand, gravel and grass.
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基于轮式机器人前后距离信息的粗糙地形表面强度频域分析
本文探讨了利用超声传感器的前后距离信息识别材料类型的可能性,该信息随表面强度的变化而变化。利用FFT将前后距离数据转换到频域,并对频域数据进行分析,提取材料类型的特征。传感器数据由一个试验台获取,用于分析四种类型表面上的车轮-地形相互作用;沥青,沙子,砾石和草。
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