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Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor
In this paper, we researched Pedestrian Dead Reckoning (PDR) with one foot-mounted IMU sensor. The issues of PDR are magnetism noise and accumulated error due to the noise included in acceleration and gyro data. Two methods are proposed in this paper. First is the gait-phase-estimation method with p...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027260/ https://www.ncbi.nlm.nih.gov/pubmed/35457914 http://dx.doi.org/10.3390/mi13040610 |
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author | Yamagishi, Shunsei Jing, Lei |
author_facet | Yamagishi, Shunsei Jing, Lei |
author_sort | Yamagishi, Shunsei |
collection | PubMed |
description | In this paper, we researched Pedestrian Dead Reckoning (PDR) with one foot-mounted IMU sensor. The issues of PDR are magnetism noise and accumulated error due to the noise included in acceleration and gyro data. Two methods are proposed in this paper. First is the gait-phase-estimation method with pitch angle for the Zero Velocity Update algorithm. Second is a method for avoiding accumulated errors by updating the roll and pitch angles with acceleration. The two experiments were conducted to examine the error of gait-phase estimation and distance estimations. The relative error of distance was about 7.40% in the case of walking straight and about 12.27% in the case of a shifting travel direction. |
format | Online Article Text |
id | pubmed-9027260 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90272602022-04-23 Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor Yamagishi, Shunsei Jing, Lei Micromachines (Basel) Article In this paper, we researched Pedestrian Dead Reckoning (PDR) with one foot-mounted IMU sensor. The issues of PDR are magnetism noise and accumulated error due to the noise included in acceleration and gyro data. Two methods are proposed in this paper. First is the gait-phase-estimation method with pitch angle for the Zero Velocity Update algorithm. Second is a method for avoiding accumulated errors by updating the roll and pitch angles with acceleration. The two experiments were conducted to examine the error of gait-phase estimation and distance estimations. The relative error of distance was about 7.40% in the case of walking straight and about 12.27% in the case of a shifting travel direction. MDPI 2022-04-13 /pmc/articles/PMC9027260/ /pubmed/35457914 http://dx.doi.org/10.3390/mi13040610 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Yamagishi, Shunsei Jing, Lei Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title | Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title_full | Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title_fullStr | Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title_full_unstemmed | Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title_short | Pedestrian Dead Reckoning with Low-Cost Foot-Mounted IMU Sensor |
title_sort | pedestrian dead reckoning with low-cost foot-mounted imu sensor |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027260/ https://www.ncbi.nlm.nih.gov/pubmed/35457914 http://dx.doi.org/10.3390/mi13040610 |
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