A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS

Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an actio...
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Gespeichert in:

Autor*in:	Ajmal Hinas [verfasserIn] Roshan Ragel [verfasserIn] Jonathan Roberts [verfasserIn] Felipe Gonzalez [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	unmanned aerial vehicle unmanned aerial system vision-based navigation search and rescue vision and action ooda inspection target detection remote sensing

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 20(2020), 1, p 272
Übergeordnetes Werk:	volume:20 ; year:2020 ; number:1, p 272

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s20010272

Katalog-ID:	DOAJ025617478

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allfieldsSound	10.3390/s20010272 doi (DE-627)DOAJ025617478 (DE-599)DOAJa9595e32ba0d450c87fa8314c40e005b DE-627 ger DE-627 rakwb eng TP1-1185 Ajmal Hinas verfasserin aut A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an action is desirable in many applications, including inspection, search and rescue and spot spraying in agriculture. This paper proposes a robust framework for vision-based ground target finding and action using the high-level decision-making approach of Observe, Orient, Decide and Act (OODA). The proposed framework was implemented as a modular software system using the robotic operating system (ROS). The framework can be effectively deployed in different applications where single or multiple target detection and action is needed. The accuracy and precision of camera-based target position estimation from a low-cost UAS is not adequate for the task due to errors and uncertainties in low-cost sensors, sensor drift and target detection errors. External disturbances such as wind also pose further challenges. The implemented framework was tested using two different test cases. Overall, the results show that the proposed framework is robust to localization and target detection errors and able to perform the task. unmanned aerial vehicle unmanned aerial system vision-based navigation search and rescue vision and action ooda inspection target detection remote sensing Chemical technology Roshan Ragel verfasserin aut Jonathan Roberts verfasserin aut Felipe Gonzalez verfasserin aut In Sensors MDPI AG, 2003 20(2020), 1, p 272 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:20 year:2020 number:1, p 272 https://doi.org/10.3390/s20010272 kostenfrei https://doaj.org/article/a9595e32ba0d450c87fa8314c40e005b kostenfrei https://www.mdpi.com/1424-8220/20/1/272 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2020 1, p 272
language	English
source	In Sensors 20(2020), 1, p 272 volume:20 year:2020 number:1, p 272
sourceStr	In Sensors 20(2020), 1, p 272 volume:20 year:2020 number:1, p 272
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institution	findex.gbv.de
topic_facet	unmanned aerial vehicle unmanned aerial system vision-based navigation search and rescue vision and action ooda inspection target detection remote sensing Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Ajmal Hinas @@aut@@ Roshan Ragel @@aut@@ Jonathan Roberts @@aut@@ Felipe Gonzalez @@aut@@
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callnumber-first	T - Technology
author	Ajmal Hinas
spellingShingle	Ajmal Hinas misc TP1-1185 misc unmanned aerial vehicle misc unmanned aerial system misc vision-based navigation misc search and rescue misc vision and action misc ooda misc inspection misc target detection misc remote sensing misc Chemical technology A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS
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topic_title	TP1-1185 A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS unmanned aerial vehicle unmanned aerial system vision-based navigation search and rescue vision and action ooda inspection target detection remote sensing
topic	misc TP1-1185 misc unmanned aerial vehicle misc unmanned aerial system misc vision-based navigation misc search and rescue misc vision and action misc ooda misc inspection misc target detection misc remote sensing misc Chemical technology
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title	A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS
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title_full	A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS
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title_auth	A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS
abstract	Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an action is desirable in many applications, including inspection, search and rescue and spot spraying in agriculture. This paper proposes a robust framework for vision-based ground target finding and action using the high-level decision-making approach of Observe, Orient, Decide and Act (OODA). The proposed framework was implemented as a modular software system using the robotic operating system (ROS). The framework can be effectively deployed in different applications where single or multiple target detection and action is needed. The accuracy and precision of camera-based target position estimation from a low-cost UAS is not adequate for the task due to errors and uncertainties in low-cost sensors, sensor drift and target detection errors. External disturbances such as wind also pose further challenges. The implemented framework was tested using two different test cases. Overall, the results show that the proposed framework is robust to localization and target detection errors and able to perform the task.
abstractGer	Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an action is desirable in many applications, including inspection, search and rescue and spot spraying in agriculture. This paper proposes a robust framework for vision-based ground target finding and action using the high-level decision-making approach of Observe, Orient, Decide and Act (OODA). The proposed framework was implemented as a modular software system using the robotic operating system (ROS). The framework can be effectively deployed in different applications where single or multiple target detection and action is needed. The accuracy and precision of camera-based target position estimation from a low-cost UAS is not adequate for the task due to errors and uncertainties in low-cost sensors, sensor drift and target detection errors. External disturbances such as wind also pose further challenges. The implemented framework was tested using two different test cases. Overall, the results show that the proposed framework is robust to localization and target detection errors and able to perform the task.
abstract_unstemmed	Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an action is desirable in many applications, including inspection, search and rescue and spot spraying in agriculture. This paper proposes a robust framework for vision-based ground target finding and action using the high-level decision-making approach of Observe, Orient, Decide and Act (OODA). The proposed framework was implemented as a modular software system using the robotic operating system (ROS). The framework can be effectively deployed in different applications where single or multiple target detection and action is needed. The accuracy and precision of camera-based target position estimation from a low-cost UAS is not adequate for the task due to errors and uncertainties in low-cost sensors, sensor drift and target detection errors. External disturbances such as wind also pose further challenges. The implemented framework was tested using two different test cases. Overall, the results show that the proposed framework is robust to localization and target detection errors and able to perform the task.
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title_short	A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS
url	https://doi.org/10.3390/s20010272 https://doaj.org/article/a9595e32ba0d450c87fa8314c40e005b https://www.mdpi.com/1424-8220/20/1/272 https://doaj.org/toc/1424-8220
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A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS

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