國立虎尾科技大學 |

Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles./
作者:	Fan, Shichen.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	79 p.
附註:	Source: Masters Abstracts International, Volume: 84-05.
Contained By:	Masters Abstracts International84-05.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29396703
ISBN:	9798357554109

Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles.
Fan, Shichen.

Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 79 p.

Source: Masters Abstracts International, Volume: 84-05.

Thesis (M.A.S.)--University of Toronto (Canada), 2022.

This item must not be sold to any third party vendors.

The primary objective of this thesis is to solve the cooperative hunting problem with multiple unmanned aerial vehicles (UAVs) in scenarios where obstacles of various sizes are in a three-dimensional (3D) static or dynamic environment while avoiding the downwash impact. This solution combines a Hungarian Vertices Assignment strategy, a 3D encirclement strategy, a novel revised particle swarm optimization (PSO) path planning algorithm, an obstacle avoidance algorithm, and a controller. Varied from the standard PSO path planning, which draws particles at random locations in random directions around the hunter agents, this revised particle swarm optimization path planning algorithm increases the computational efficiency in finding the trajectory and next position for each hunter agent by initializing the particle swarm along the direction toward the goal position. Simulation results show that the solution successfully hunts and encircles a moving or stationary target simultaneously in a dynamic or static obstacle-rich cluttered environment.

ISBN: 9798357554109Subjects--Topical Terms:

561152
Engineering.
Subjects--Index Terms:

Control system

Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles.
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245 1 0 $a Multi-UAV Cooperative Hunting in Three-Dimensional Environment with Obstacles.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2022
300 $a 79 p.
500 $a Source: Masters Abstracts International, Volume: 84-05.
500 $a Includes supplementary digital materials.
500 $a Advisor: Liu, Hugh H. T.
502 $a Thesis (M.A.S.)--University of Toronto (Canada), 2022.
506 $a This item must not be sold to any third party vendors.
520 $a The primary objective of this thesis is to solve the cooperative hunting problem with multiple unmanned aerial vehicles (UAVs) in scenarios where obstacles of various sizes are in a three-dimensional (3D) static or dynamic environment while avoiding the downwash impact. This solution combines a Hungarian Vertices Assignment strategy, a 3D encirclement strategy, a novel revised particle swarm optimization (PSO) path planning algorithm, an obstacle avoidance algorithm, and a controller. Varied from the standard PSO path planning, which draws particles at random locations in random directions around the hunter agents, this revised particle swarm optimization path planning algorithm increases the computational efficiency in finding the trajectory and next position for each hunter agent by initializing the particle swarm along the direction toward the goal position. Simulation results show that the solution successfully hunts and encircles a moving or stationary target simultaneously in a dynamic or static obstacle-rich cluttered environment.
590 $a School code: 0779.
650 4 $a Engineering. $3 561152
650 4 $a Computer engineering. $3 569006
650 4 $a Aerospace engineering. $3 686400
653 $a Control system
653 $a Cooperative hunting
653 $a Downwash impact
653 $a Drone
653 $a Path planning
653 $a UAV
653 $a Unmanned aerial vehicle
690 $a 0537
690 $a 0464
690 $a 0538
710 2 $a University of Toronto (Canada). $b Aerospace Science and Engineering. $3 845686
773 0 $t Masters Abstracts International $g 84-05.
790 $a 0779
791 $a M.A.S.
792 $a 2022
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29396703