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Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data
This article compares three different algorithms used to compute Euler angles from data obtained by the angular rate sensor (e.g., MEMS gyroscope)—the algorithms based on a rotational matrix, on transforming angular velocity to time derivations of the Euler angles and on unit quaternion expressing r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435132/ https://www.ncbi.nlm.nih.gov/pubmed/25806874 http://dx.doi.org/10.3390/s150307016 |
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author | Janota, Aleš Šimák, Vojtech Nemec, Dušan Hrbček, Jozef |
author_facet | Janota, Aleš Šimák, Vojtech Nemec, Dušan Hrbček, Jozef |
author_sort | Janota, Aleš |
collection | PubMed |
description | This article compares three different algorithms used to compute Euler angles from data obtained by the angular rate sensor (e.g., MEMS gyroscope)—the algorithms based on a rotational matrix, on transforming angular velocity to time derivations of the Euler angles and on unit quaternion expressing rotation. Algorithms are compared by their computational efficiency and accuracy of Euler angles estimation. If attitude of the object is computed only from data obtained by the gyroscope, the quaternion-based algorithm seems to be most suitable (having similar accuracy as the matrix-based algorithm, but taking approx. 30% less clock cycles on the 8-bit microcomputer). Integration of the Euler angles’ time derivations has a singularity, therefore is not accurate at full range of object’s attitude. Since the error in every real gyroscope system tends to increase with time due to its offset and thermal drift, we also propose some measures based on compensation by additional sensors (a magnetic compass and accelerometer). Vector data of mentioned secondary sensors has to be transformed into the inertial frame of reference. While transformation of the vector by the matrix is slightly faster than doing the same by quaternion, the compensated sensor system utilizing a matrix-based algorithm can be approximately 10% faster than the system utilizing quaternions (depending on implementation and hardware). |
format | Online Article Text |
id | pubmed-4435132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-44351322015-05-19 Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data Janota, Aleš Šimák, Vojtech Nemec, Dušan Hrbček, Jozef Sensors (Basel) Article This article compares three different algorithms used to compute Euler angles from data obtained by the angular rate sensor (e.g., MEMS gyroscope)—the algorithms based on a rotational matrix, on transforming angular velocity to time derivations of the Euler angles and on unit quaternion expressing rotation. Algorithms are compared by their computational efficiency and accuracy of Euler angles estimation. If attitude of the object is computed only from data obtained by the gyroscope, the quaternion-based algorithm seems to be most suitable (having similar accuracy as the matrix-based algorithm, but taking approx. 30% less clock cycles on the 8-bit microcomputer). Integration of the Euler angles’ time derivations has a singularity, therefore is not accurate at full range of object’s attitude. Since the error in every real gyroscope system tends to increase with time due to its offset and thermal drift, we also propose some measures based on compensation by additional sensors (a magnetic compass and accelerometer). Vector data of mentioned secondary sensors has to be transformed into the inertial frame of reference. While transformation of the vector by the matrix is slightly faster than doing the same by quaternion, the compensated sensor system utilizing a matrix-based algorithm can be approximately 10% faster than the system utilizing quaternions (depending on implementation and hardware). MDPI 2015-03-23 /pmc/articles/PMC4435132/ /pubmed/25806874 http://dx.doi.org/10.3390/s150307016 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Janota, Aleš Šimák, Vojtech Nemec, Dušan Hrbček, Jozef Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title | Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title_full | Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title_fullStr | Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title_full_unstemmed | Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title_short | Improving the Precision and Speed of Euler Angles Computation from Low-Cost Rotation Sensor Data |
title_sort | improving the precision and speed of euler angles computation from low-cost rotation sensor data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4435132/ https://www.ncbi.nlm.nih.gov/pubmed/25806874 http://dx.doi.org/10.3390/s150307016 |
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