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Algorithms for routing unmanned vehicles with motions, resource, and communication constraints.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Algorithms for routing unmanned vehicles with motions, resource, and communication constraints./
Author:	Sundar, Kaarthik.
Description:	1 online resource (135 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
Contained By:	Dissertation Abstracts International78-02B(E).
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781339990859

Algorithms for routing unmanned vehicles with motions, resource, and communication constraints.
Sundar, Kaarthik.

Algorithms for routing unmanned vehicles with motions, resource, and communication constraints. - 1 online resource (135 pages)

Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Multiple small autonomous or unmanned aerial and ground vehicles are being used together with stationary sensing devices for a wide variety of data gathering, monitoring and surveillance applications in military, civilian, and agricultural applications, to name a few. Even though there are several advantages due to the small platforms for these vehicles, they pose a variety of challenges. This dissertation aims to address the following challenges to routing multiple small autonomous aerial or ground vehicles: (i) limited communication capabilities of the stationary sensing devices, (ii) dynamics of the vehicles, (iii) varying sensing capabilities of all the vehicles, and (iv) resource constraints in the form of fuel restrictions on each vehicle. The dissertation formulates four different routing problems for multiple unmanned vehicles, one for each of the aforementioned constraints, as mixed-integer linear programs and develops numerically efficient algorithms based on the branch-and-cut paradigm to compute optimal solutions for practically reasonable size of test instances.

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

Mode of access: World Wide Web

ISBN: 9781339990859Subjects--Topical Terms:

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

554714
Electronic books.

Algorithms for routing unmanned vehicles with motions, resource, and communication constraints.
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245 1 0 $a Algorithms for routing unmanned vehicles with motions, resource, and communication constraints.
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500 $a Source: Dissertation Abstracts International, Volume: 78-02(E), Section: B.
500 $a Adviser: Sivakumar Rathinam.
502 $a Thesis (Ph.D.) $c Texas A&M University $d 2016.
504 $a Includes bibliographical references
520 $a Multiple small autonomous or unmanned aerial and ground vehicles are being used together with stationary sensing devices for a wide variety of data gathering, monitoring and surveillance applications in military, civilian, and agricultural applications, to name a few. Even though there are several advantages due to the small platforms for these vehicles, they pose a variety of challenges. This dissertation aims to address the following challenges to routing multiple small autonomous aerial or ground vehicles: (i) limited communication capabilities of the stationary sensing devices, (ii) dynamics of the vehicles, (iii) varying sensing capabilities of all the vehicles, and (iv) resource constraints in the form of fuel restrictions on each vehicle. The dissertation formulates four different routing problems for multiple unmanned vehicles, one for each of the aforementioned constraints, as mixed-integer linear programs and develops numerically efficient algorithms based on the branch-and-cut paradigm to compute optimal solutions for practically reasonable size of test instances.
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 Robotics. $3 561941
650 4 $a Industrial engineering. $3 679492
655 7 $a Electronic books. $2 local $3 554714
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710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Texas A&M University. $b Mechanical Engineering. $3 1180218
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