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Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot
For use in autonomous micro air vehicles, visual sensors must not only be small, lightweight and insensitive to light variations; on-board autopilots also require fast and accurate optical flow measurements over a wide range of speeds. Using an auto-adaptive bio-inspired Michaelis–Menten Auto-adapti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375857/ https://www.ncbi.nlm.nih.gov/pubmed/28287484 http://dx.doi.org/10.3390/s17030571 |
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author | Vanhoutte, Erik Mafrica, Stefano Ruffier, Franck Bootsma, Reinoud J. Serres, Julien |
author_facet | Vanhoutte, Erik Mafrica, Stefano Ruffier, Franck Bootsma, Reinoud J. Serres, Julien |
author_sort | Vanhoutte, Erik |
collection | PubMed |
description | For use in autonomous micro air vehicles, visual sensors must not only be small, lightweight and insensitive to light variations; on-board autopilots also require fast and accurate optical flow measurements over a wide range of speeds. Using an auto-adaptive bio-inspired Michaelis–Menten Auto-adaptive Pixel (M [Formula: see text] APix) analog silicon retina, in this article, we present comparative tests of two optical flow calculation algorithms operating under lighting conditions from [Formula: see text] to [Formula: see text] W·cm [Formula: see text] (i.e., from 0.2 to 12,000 lux for human vision). Contrast “time of travel” between two adjacent light-sensitive pixels was determined by thresholding and by cross-correlating the two pixels’ signals, with measurement frequency up to 5 kHz for the 10 local motion sensors of the M [Formula: see text] APix sensor. While both algorithms adequately measured optical flow between 25 [Formula: see text] /s and 1000 [Formula: see text] /s, thresholding gave rise to a lower precision, especially due to a larger number of outliers at higher speeds. Compared to thresholding, cross-correlation also allowed for a higher rate of optical flow output (99 Hz and 1195 Hz, respectively) but required substantially more computational resources. |
format | Online Article Text |
id | pubmed-5375857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-53758572017-04-10 Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot Vanhoutte, Erik Mafrica, Stefano Ruffier, Franck Bootsma, Reinoud J. Serres, Julien Sensors (Basel) Article For use in autonomous micro air vehicles, visual sensors must not only be small, lightweight and insensitive to light variations; on-board autopilots also require fast and accurate optical flow measurements over a wide range of speeds. Using an auto-adaptive bio-inspired Michaelis–Menten Auto-adaptive Pixel (M [Formula: see text] APix) analog silicon retina, in this article, we present comparative tests of two optical flow calculation algorithms operating under lighting conditions from [Formula: see text] to [Formula: see text] W·cm [Formula: see text] (i.e., from 0.2 to 12,000 lux for human vision). Contrast “time of travel” between two adjacent light-sensitive pixels was determined by thresholding and by cross-correlating the two pixels’ signals, with measurement frequency up to 5 kHz for the 10 local motion sensors of the M [Formula: see text] APix sensor. While both algorithms adequately measured optical flow between 25 [Formula: see text] /s and 1000 [Formula: see text] /s, thresholding gave rise to a lower precision, especially due to a larger number of outliers at higher speeds. Compared to thresholding, cross-correlation also allowed for a higher rate of optical flow output (99 Hz and 1195 Hz, respectively) but required substantially more computational resources. MDPI 2017-03-11 /pmc/articles/PMC5375857/ /pubmed/28287484 http://dx.doi.org/10.3390/s17030571 Text en © 2017 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vanhoutte, Erik Mafrica, Stefano Ruffier, Franck Bootsma, Reinoud J. Serres, Julien Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title | Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title_full | Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title_fullStr | Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title_full_unstemmed | Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title_short | Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot |
title_sort | time-of-travel methods for measuring optical flow on board a micro flying robot |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375857/ https://www.ncbi.nlm.nih.gov/pubmed/28287484 http://dx.doi.org/10.3390/s17030571 |
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