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GPS-denied multi-agent localization ...

ProQuest Information and Learning Co.

GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems./
Author:	Chiel, Benjamin S.
Description:	1 online resource (107 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
Contained By:	Dissertation Abstracts International78-05B(E).
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781369357806

GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems.
Chiel, Benjamin S.

GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems. - 1 online resource (107 pages)

Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Guided airdrop parafoil systems depend on GPS for localization and landing. In some scenarios, GPS may be unreliable (jammed, spoofed, or disabled), or unavailable (indoor, or extraterrestrial environments). In the context of guided parafoils, landing locations for each system must be pre-programmed manually with global coordinates, which may be inaccurate or outdated, and offer no in-flight adaptability. Parafoil systems in particular have constrained motion, communication, and on-board computation and storage capabilities, and must operate in harsh conditions. These constraints necessitate a comprehensive approach to address the fundamental limitations of these systems when GPS cannot be used reliably. A novel and minimalist approach to visual navigation and multi-agent communication using semantic machine learning classification and geometric constraints is introduced. This approach enables localization and landing site identification for multiple communicating parafoil systems deployed in GPS-denied environments.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369357806Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems.
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245 1 0 $a GPS-denied multi-agent localization and terrain classification for autonomous parafoil systems.
264 0 $c 2016
300 $a 1 online resource (107 pages)
336 $a text $b txt $2 rdacontent
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500 $a Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
500 $a Adviser: John Baillieul.
502 $a Thesis (Ph.D.) $c Boston University $d 2016.
504 $a Includes bibliographical references
520 $a Guided airdrop parafoil systems depend on GPS for localization and landing. In some scenarios, GPS may be unreliable (jammed, spoofed, or disabled), or unavailable (indoor, or extraterrestrial environments). In the context of guided parafoils, landing locations for each system must be pre-programmed manually with global coordinates, which may be inaccurate or outdated, and offer no in-flight adaptability. Parafoil systems in particular have constrained motion, communication, and on-board computation and storage capabilities, and must operate in harsh conditions. These constraints necessitate a comprehensive approach to address the fundamental limitations of these systems when GPS cannot be used reliably. A novel and minimalist approach to visual navigation and multi-agent communication using semantic machine learning classification and geometric constraints is introduced. This approach enables localization and landing site identification for multiple communicating parafoil systems deployed in GPS-denied environments.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Artificial intelligence. $3 559380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0800
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Boston University. $b Mechanical Engineering. $3 1148636
773 0 $t Dissertation Abstracts International $g 78-05B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10193490 $z click for full text (PQDT)

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