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Task allocation and path planning fo...

Deng, Yueyue.

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Task allocation and path planning for acoustic networks of AUVs.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Task allocation and path planning for acoustic networks of AUVs./
Author:	Deng, Yueyue.
Description:	171 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-05, Section: B, page: 3283.
Contained By:	Dissertation Abstracts International71-05B.
Subject:	Engineering, Computer. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3406830
ISBN:	9781109739695

Task allocation and path planning for acoustic networks of AUVs.
Deng, Yueyue.

Task allocation and path planning for acoustic networks of AUVs. - 171 p.

Source: Dissertation Abstracts International, Volume: 71-05, Section: B, page: 3283.

Thesis (Ph.D.)--Florida Atlantic University, 2010.

Controlling the cooperative behaviors of a fleet of autonomous underwater vehicles in a stochastic, complex environment is a formidable challenge in artificial intelligence. The complexity arises from the challenges of limited navigation and communication capabilities of underwater environment. A time critical cooperative operation by acoustic networks of Multiple Cooperative Vehicles (MCVs) necessitates a robust task allocation mechanism and an efficient path planning model. In this work, we present solutions to investigate two aspects of the cooperative schema for multiple underwater vehicles under realistic underwater acoustic communications: a Location-aided Task Allocation Framework (LAAF) algorithm for multi-target task assignment and a mathematical programming model, the Grid-based Multi-Objective Optimal Programming (GMOOP), for finding an optimal vehicle command decision given a set of objectives and constraints. We demonstrate that, the location-aided auction strategies perform significantly better than the generic auction algorithm in terms of effective task allocation time and information bandwidth requirements. In a typical task assignment scenario, the time needed in the LAAF algorithm is only a fraction compared to the generic auction algorithm. On the other hand; the GMOOP path planning technique provides a unique means for multi-objective tasks by cooperative agents with limited communication capabilities. Under different environmental settings, the GMOOP path planning technique is proved to provide a method with balance of sufficient expressive power and flexibility, and its solution algorithms tractable in terms of mission completion time, with a limited increase of overhead in acoustic communication. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant communication available. The dynamic task allocation, together with the GMOOP path planning controller, provides a comprehensive solution to the search-classify tasks for cooperative AUVs.

ISBN: 9781109739695Subjects--Topical Terms:

1669061
Engineering, Computer.

Task allocation and path planning for acoustic networks of AUVs.
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035 $a (UMI)AAI3406830
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100 1 $a Deng, Yueyue. $3 1684455
245 1 0 $a Task allocation and path planning for acoustic networks of AUVs.
300 $a 171 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-05, Section: B, page: 3283.
500 $a Adviser: Pierre-Philippe Beaujean.
502 $a Thesis (Ph.D.)--Florida Atlantic University, 2010.
520 $a Controlling the cooperative behaviors of a fleet of autonomous underwater vehicles in a stochastic, complex environment is a formidable challenge in artificial intelligence. The complexity arises from the challenges of limited navigation and communication capabilities of underwater environment. A time critical cooperative operation by acoustic networks of Multiple Cooperative Vehicles (MCVs) necessitates a robust task allocation mechanism and an efficient path planning model. In this work, we present solutions to investigate two aspects of the cooperative schema for multiple underwater vehicles under realistic underwater acoustic communications: a Location-aided Task Allocation Framework (LAAF) algorithm for multi-target task assignment and a mathematical programming model, the Grid-based Multi-Objective Optimal Programming (GMOOP), for finding an optimal vehicle command decision given a set of objectives and constraints. We demonstrate that, the location-aided auction strategies perform significantly better than the generic auction algorithm in terms of effective task allocation time and information bandwidth requirements. In a typical task assignment scenario, the time needed in the LAAF algorithm is only a fraction compared to the generic auction algorithm. On the other hand; the GMOOP path planning technique provides a unique means for multi-objective tasks by cooperative agents with limited communication capabilities. Under different environmental settings, the GMOOP path planning technique is proved to provide a method with balance of sufficient expressive power and flexibility, and its solution algorithms tractable in terms of mission completion time, with a limited increase of overhead in acoustic communication. Prior to this work, existing multi-objective action selection methods were limited to robust networks where constant communication available. The dynamic task allocation, together with the GMOOP path planning controller, provides a comprehensive solution to the search-classify tasks for cooperative AUVs.
590 $a School code: 0119.
650 4 $a Engineering, Computer. $3 1669061
650 4 $a Engineering, Marine and Ocean. $3 1019064
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0464
690 $a 0547
690 $a 0771
710 2 $a Florida Atlantic University. $3 1017837
773 0 $t Dissertation Abstracts International $g 71-05B.
790 1 0 $a Beaujean, Pierre-Philippe, $e advisor
790 $a 0119
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3406830