東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Efficient, cooperative multirobot te...

Anderson, Monica Delaine.

Linked to FindBook

Google Book

Amazon

博客來

Efficient, cooperative multirobot team search in complex indoor environments.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Efficient, cooperative multirobot team search in complex indoor environments./
Author:	Anderson, Monica Delaine.
Description:	112 p.
Notes:	Adviser: Nikolaos Papanikolopoulos.
Contained By:	Dissertation Abstracts International68-07B.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3273171
ISBN:	9780549116783

Efficient, cooperative multirobot team search in complex indoor environments.
Anderson, Monica Delaine.

Efficient, cooperative multirobot team search in complex indoor environments. - 112 p.

Adviser: Nikolaos Papanikolopoulos.

Thesis (Ph.D.)--University of Minnesota, 2007.

Distributed robot teams have become ubiquitous. Robots are less expensive, more powerful, and easier to program. When distributed robot teams are used for surveillance, search and rescue missions, the distance between humans and danger can be increased. Robot-assisted search in an unknown environment is a critical component in all of these missions. There is little question that using a team of robots can improve the efficiency of a search task over using a single robot. However, design choices multiply when organizing a multirobot team to achieve a balance between flexibility, cost and coverage. Recently, proposed distributed coverage algorithms either share a global world representation that is used to determine subsequent search targets or coordinate explicitly via communicating specific task information. The resulting algorithms either rely too heavily on less than accurate information from team members or limit team size due to large communications overhead.

ISBN: 9780549116783Subjects--Topical Terms:

626642
Computer Science.

Efficient, cooperative multirobot team search in complex indoor environments.
LDR:02672nam 2200289 a 45 001 940666
005 20110518
008 110518s2007 ||||||||||||||||| ||eng d
020 $a 9780549116783
035 $a (UMI)AAI3273171
035 $a AAI3273171
040 $a UMI $c UMI
100 1 $a Anderson, Monica Delaine. $3 1264798
245 1 0 $a Efficient, cooperative multirobot team search in complex indoor environments.
300 $a 112 p.
500 $a Adviser: Nikolaos Papanikolopoulos.
500 $a Source: Dissertation Abstracts International, Volume: 68-07, Section: B, page: 4580.
502 $a Thesis (Ph.D.)--University of Minnesota, 2007.
520 $a Distributed robot teams have become ubiquitous. Robots are less expensive, more powerful, and easier to program. When distributed robot teams are used for surveillance, search and rescue missions, the distance between humans and danger can be increased. Robot-assisted search in an unknown environment is a critical component in all of these missions. There is little question that using a team of robots can improve the efficiency of a search task over using a single robot. However, design choices multiply when organizing a multirobot team to achieve a balance between flexibility, cost and coverage. Recently, proposed distributed coverage algorithms either share a global world representation that is used to determine subsequent search targets or coordinate explicitly via communicating specific task information. The resulting algorithms either rely too heavily on less than accurate information from team members or limit team size due to large communications overhead.
520 $a In this thesis, the repertoire of available search algorithms is expanded to include novel, biologically inspired approaches to coverage and coordination. Although many approaches implement footprint coverage (e.g., mine-sweeping), algorithmic changes expand search to use any arbitrary search sensor. Robots looking for chemicals or animals, can cover an unknown environment using a chemical or heat sensor with on-line planning. In addition, coordination using local search queues, rather than globally shared search queues is shown to improve search in terms of interference, communications loads and sensitivity to localization errors, three key factors in multirobot search. Both simulations and experiments are presented to support the efficacy of the novel approaches.
590 $a School code: 0130.
650 4 $a Computer Science. $3 626642
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
690 $a 0984
710 2 $a University of Minnesota. $3 676231
773 0 $t Dissertation Abstracts International $g 68-07B.
790 $a 0130
790 1 0 $a Papanikolopoulos, Nikolaos, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3273171