Step Length Is a More Reliable Measurement Than Walking Speed for Pedestrian Dead-Reckoning.

Fatemeh Elyasi, Roberto Manduchi
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Abstract

Pedestrian dead reckoning (PDR) relies on the estimation of the length of each step taken by the walker in a path from inertial data (e.g. as recorded by a smartphone). Existing algorithms either estimate step lengths directly, or predict walking speed, which can then be integrated over a step period to obtain step length. We present an analysis, using a common architecture formed by an LSTM followed by four fully connected layers, of the quality of reconstruction when predicting step length vs. walking speed. Our experiments, conducted on a data set collected by twelve participants, strongly suggest that step length can be predicted more reliably than average walking speed over each step.

步长是比步行速度更可靠的行人死角测量方法。
行人惯性推算(PDR)依靠惯性数据(如智能手机记录的数据)估算步行者在路径上每一步的长度。现有的算法要么直接估算步长,要么预测行走速度,然后将行走速度与步长周期进行整合,得出步长。我们使用一个由 LSTM 和四个全连接层组成的通用架构,对预测步长与步行速度时的重构质量进行了分析。我们在 12 名参与者收集的数据集上进行了实验,结果强烈表明,预测步长比预测每一步的平均步行速度更可靠。
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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