Trajectory planning for effective close-proximity sensing with agile vehicles [electronic resource] / Baron Jon Johnson

Johnson, Baron Jon.
Bib ID
vtls000456451
出版項
Ann Arbor, Mich. : ProQuest Information and learning
稽核項
232 p.
電子版
附註項
數位化論文典藏聯盟
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$a Johnson, Baron Jon.
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$a Trajectory planning for effective close-proximity sensing with agile vehicles $h [electronic resource] / $c Baron Jon Johnson
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$a Ann Arbor, Mich. : $b ProQuest Information and learning
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$a 232 p.
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$a Source: Dissertation Abstracts International, Volume: 72-10, Section: B, page: .
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$a Adviser: Richard C. Lind, Jr.
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$a Thesis (Ph.D.)--University of Florida, 2011.
520
$a Unmanned systems are expected to continue growing in usefulness for surveillance missions. Advancing technology in vehicle maneuverability and miniature control systems is allowing new sensing missions to be considered where the vehicle operates in close proximity to the targets it is sensing. This presents challenges not present in stand-off sensing missions commonly performed by unmanned systems. Vehicle motion is directly linked to sensing quality and thus must be considered in the mission-planning phase to ensure adequate sensing is performed.
520
$a This dissertation presents a methodology for generating kinematically feasible trajectories through cluttered environments which satisfy sensing effectiveness requirements for multiple targets. Vehicles carrying a single line-of-sight (LOS) sensor are considered and the coupling between vehicle motion and sensor orientation is explicitly addressed. Algorithms are introduced which improve upon the required path time while preserving the sensing effectiveness. Surrogate modeling is also introduced as a method to improve trajectories in terms of any specified cost function.
520
$a The sensor-based path planning framework is adapted for a highly agile unmanned aircraft capable of flying at high angles-of-attack and the results are presented as an example of the usefulness of these trajectory planning techniques. The inclusion of the unique high angle-of-attack flight capability is shown to provide improvements in both the sensing effectiveness and the overall path time.
591
$a 數位化論文典藏聯盟 $b PQDT $c 淡江大學(2012)
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$a Engineering, Aerospace.
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$a Engineering, Robotics.
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$a University of Florida.
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$a Dissertation Abstracts International ; $v 72-10B
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$u http://info.lib.tku.edu.tw/ebook/redirect.asp?bibid=456451
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叢書名
Dissertation Abstracts International ; 72-10B
摘要
Unmanned systems are expected to continue growing in usefulness for surveillance missions. Advancing technology in vehicle maneuverability and miniature control systems is allowing new sensing missions to be considered where the vehicle operates in close proximity to the targets it is sensing. This presents challenges not present in stand-off sensing missions commonly performed by unmanned systems. Vehicle motion is directly linked to sensing quality and thus must be considered in the mission-planning phase to ensure adequate sensing is performed.
This dissertation presents a methodology for generating kinematically feasible trajectories through cluttered environments which satisfy sensing effectiveness requirements for multiple targets. Vehicles carrying a single line-of-sight (LOS) sensor are considered and the coupling between vehicle motion and sensor orientation is explicitly addressed. Algorithms are introduced which improve upon the required path time while preserving the sensing effectiveness. Surrogate modeling is also introduced as a method to improve trajectories in terms of any specified cost function.
The sensor-based path planning framework is adapted for a highly agile unmanned aircraft capable of flying at high angles-of-attack and the results are presented as an example of the usefulness of these trajectory planning techniques. The inclusion of the unique high angle-of-attack flight capability is shown to provide improvements in both the sensing effectiveness and the overall path time.
附註
Source: Dissertation Abstracts International, Volume: 72-10, Section: B, page: .
Adviser: Richard C. Lind, Jr.
Thesis (Ph.D.)--University of Florida, 2011.
數位化論文典藏聯盟
合著者
ISBN/ISSN
9781124795768