Mahalanobis distance-based road condition estimation method using network-connected manual wheelchair

K. Kojima, Hiroki Taniue, J. Kaneko
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引用次数: 9

Abstract

This paper describes a method to estimate road condition using our developed network-connected manual wheelchair. We have been developing the wheelchair on which torque sensors, an accelerometer and a GPS receiver are implemented, for gathering the road condition data onto our server PC. Our final purpose is to develop a system which display traffic disturbances for manual wheelchairs on the digital map automatically. For this purpose, this study aims to associate the sensor values with road conditions using Mahalanobis distance. In this paper, firstly, our developed wheelchair is explained briefly. Then, characteristics of acquired data is shown. After that, definition of unit space for this problem and calculation of Maharanobis distance are described. Finally, possibility of categorizing road conditions using the Maharanobis distance defined by significance level is explained in detail with the experimental data.
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基于马氏距离的联网手动轮椅路况估计方法
本文介绍了一种利用自行研制的联网手动轮椅进行路况估计的方法。我们一直在开发轮椅,轮椅上安装了扭矩传感器、加速度计和GPS接收器,用于将路况数据收集到我们的服务器PC上。我们的最终目的是开发一种在数字地图上自动显示手动轮椅交通干扰的系统。为此,本研究旨在利用马氏距离将传感器值与路况联系起来。本文首先简要介绍了我国研制的轮椅。然后,给出了采集数据的特征。然后,给出了该问题的单位空间的定义和马氏距离的计算。最后,结合实验数据详细说明了利用显著性水平定义的马氏距离对路况进行分类的可能性。
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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