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Energy-Aware Path Planning for Fixed-Wing Seaplane UAVs.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Energy-Aware Path Planning for Fixed-Wing Seaplane UAVs./
Author:	Wolsieffer, Ben.
Description:	1 online resource (65 pages)
Notes:	Source: Masters Abstracts International, Volume: 85-05.
Contained By:	Masters Abstracts International85-05.
Subject:	Aircraft. -
Online resource:	click for full text (PQDT)
ISBN:	9798380875509

Energy-Aware Path Planning for Fixed-Wing Seaplane UAVs.
Wolsieffer, Ben.

Energy-Aware Path Planning for Fixed-Wing Seaplane UAVs. - 1 online resource (65 pages)

Source: Masters Abstracts International, Volume: 85-05.

Thesis (M.S.)--Dartmouth College, 2023.

Includes bibliographical references

Fixed-wing unmanned aerial vehicles (UAVs) are commonly used for remote sensing applications over water bodies, such as monitoring water quality or tracking harmful algal blooms. However, there are some types of measurements that are difficult to accurately obtain from the air. In existing work, water samples have been collected in situ either by hand, with an unmanned surface vehicle (USV), or with a vertical takeoff and landing (VTOL) UAV such as a multirotor. We propose a path planner, landing control algorithm, and energy estimator that will allow a low-cost and energy efficient fixed-wing UAV to carry out a combined remote sensing and direct water sampling mission without requiring sophisticated sensors and using limited onboard computation. Finally, we demonstrate a fully autonomous mission on a modified off-the-shelf RC aircraft. The aircraft flies a survey pattern, lands at a series of sampling points and then returns to the starting location while respecting the available energy budget. In our experiments, we completed multiple sampling missions in the real world with no aborted landings or crashes and an overall energy estimation error of approximately 5%.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380875509Subjects--Topical Terms:

580976
Aircraft.
Index Terms--Genre/Form:

554714
Electronic books.

Energy-Aware Path Planning for Fixed-Wing Seaplane UAVs.
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500 $a Source: Masters Abstracts International, Volume: 85-05.
500 $a Advisor: Li, Alberto Quattrini;Pediredla, Adithya;Ray, Laura.
502 $a Thesis (M.S.)--Dartmouth College, 2023.
504 $a Includes bibliographical references
520 $a Fixed-wing unmanned aerial vehicles (UAVs) are commonly used for remote sensing applications over water bodies, such as monitoring water quality or tracking harmful algal blooms. However, there are some types of measurements that are difficult to accurately obtain from the air. In existing work, water samples have been collected in situ either by hand, with an unmanned surface vehicle (USV), or with a vertical takeoff and landing (VTOL) UAV such as a multirotor. We propose a path planner, landing control algorithm, and energy estimator that will allow a low-cost and energy efficient fixed-wing UAV to carry out a combined remote sensing and direct water sampling mission without requiring sophisticated sensors and using limited onboard computation. Finally, we demonstrate a fully autonomous mission on a modified off-the-shelf RC aircraft. The aircraft flies a survey pattern, lands at a series of sampling points and then returns to the starting location while respecting the available energy budget. In our experiments, we completed multiple sampling missions in the real world with no aborted landings or crashes and an overall energy estimation error of approximately 5%.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Aircraft. $3 580976
650 4 $a Cameras. $3 812890
650 4 $a Remote sensing. $3 557272
650 4 $a Control algorithms. $3 1372652
650 4 $a Computer science. $3 573171
650 4 $a Planning. $3 660157
650 4 $a Sensors. $3 1003702
650 4 $a Unmanned aerial vehicles. $3 1372845
650 4 $a Vehicles. $3 721652
650 4 $a Aerospace engineering. $3 686400
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0799
690 $a 0538
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710 2 $a Dartmouth College. $b Computer Science. $3 1182313
773 0 $t Masters Abstracts International $g 85-05.
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