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Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study
Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233705/ https://www.ncbi.nlm.nih.gov/pubmed/34207193 http://dx.doi.org/10.3390/s21124186 |
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author | Tanveer, Muhammad Hassan Thomas, Antony Ahmed, Waqar Zhu, Hongxiao |
author_facet | Tanveer, Muhammad Hassan Thomas, Antony Ahmed, Waqar Zhu, Hongxiao |
author_sort | Tanveer, Muhammad Hassan |
collection | PubMed |
description | Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batch processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage. |
format | Online Article Text |
id | pubmed-8233705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82337052021-06-27 Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study Tanveer, Muhammad Hassan Thomas, Antony Ahmed, Waqar Zhu, Hongxiao Sensors (Basel) Article Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batch processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage. MDPI 2021-06-18 /pmc/articles/PMC8233705/ /pubmed/34207193 http://dx.doi.org/10.3390/s21124186 Text en © 2021 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 Tanveer, Muhammad Hassan Thomas, Antony Ahmed, Waqar Zhu, Hongxiao Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title | Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title_full | Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title_fullStr | Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title_full_unstemmed | Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title_short | Estimate the Unknown Environment with Biosonar Echoes—A Simulation Study |
title_sort | estimate the unknown environment with biosonar echoes—a simulation study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233705/ https://www.ncbi.nlm.nih.gov/pubmed/34207193 http://dx.doi.org/10.3390/s21124186 |
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