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Online Aerial Terrain Mapping for Ground Robot Navigation

This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain class...

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Detalles Bibliográficos
Autores principales: Peterson, John, Chaudhry, Haseeb, Abdelatty, Karim, Bird, John, Kochersberger, Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855888/
https://www.ncbi.nlm.nih.gov/pubmed/29461496
http://dx.doi.org/10.3390/s18020630
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author Peterson, John
Chaudhry, Haseeb
Abdelatty, Karim
Bird, John
Kochersberger, Kevin
author_facet Peterson, John
Chaudhry, Haseeb
Abdelatty, Karim
Bird, John
Kochersberger, Kevin
author_sort Peterson, John
collection PubMed
description This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles.
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spelling pubmed-58558882018-03-20 Online Aerial Terrain Mapping for Ground Robot Navigation Peterson, John Chaudhry, Haseeb Abdelatty, Karim Bird, John Kochersberger, Kevin Sensors (Basel) Article This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle’s overhead view to inform the ground vehicle’s path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles. This paper describes the architecture of the system and quantifies the registration errors between the vehicles. MDPI 2018-02-20 /pmc/articles/PMC5855888/ /pubmed/29461496 http://dx.doi.org/10.3390/s18020630 Text en © 2018 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
Peterson, John
Chaudhry, Haseeb
Abdelatty, Karim
Bird, John
Kochersberger, Kevin
Online Aerial Terrain Mapping for Ground Robot Navigation
title Online Aerial Terrain Mapping for Ground Robot Navigation
title_full Online Aerial Terrain Mapping for Ground Robot Navigation
title_fullStr Online Aerial Terrain Mapping for Ground Robot Navigation
title_full_unstemmed Online Aerial Terrain Mapping for Ground Robot Navigation
title_short Online Aerial Terrain Mapping for Ground Robot Navigation
title_sort online aerial terrain mapping for ground robot navigation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855888/
https://www.ncbi.nlm.nih.gov/pubmed/29461496
http://dx.doi.org/10.3390/s18020630
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