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Mobile robot localization failure re...

University of Windsor (Canada).

Mobile robot localization failure recovery.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Mobile robot localization failure recovery./
Author:	Seifzadeh, Sepideh.
Description:	1 online resource (54 pages)
Notes:	Source: Masters Abstracts International, Volume: 49-01, page: 4990.
Contained By:	Masters Abstracts International49-01.
Subject:	Computer science. -
Online resource:	click for full text (PQDT)
ISBN:	9780494627365

Mobile robot localization failure recovery.
Seifzadeh, Sepideh.

Mobile robot localization failure recovery. - 1 online resource (54 pages)

Source: Masters Abstracts International, Volume: 49-01, page: 4990.

Thesis (M.A.Sc.)

Includes bibliographical references

Mobile robot localization is one of the most important problems in robotics. Localization is the process of a robot finding out its location given a map of its environment. A number of successful localization solutions have been proposed, among them the well-known and popular Monte Carlo localization method, which is based on particle filters. This thesis proposes a localization approach based on particle filters, using a different way of initializing and resampling of the particles, that reduces the cost of localization. Ultrasonic and light sensors are used in order to perform the experiments. Monte Carlo Localization may fail to localize the robot properly because of the premature convergence of the particles. Using more number of particles increases the computational cost of localization process. Experimental results show that, applying the proposed method robot can successfully localize itself using less number of particles; therefore the cost of localization is decreased.

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

Mode of access: World Wide Web

ISBN: 9780494627365Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Mobile robot localization failure recovery.
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035 $a (MiAaPQ)AAIMR62736
035 $a AAIMR62736
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099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Seifzadeh, Sepideh. $3 1182102
245 1 0 $a Mobile robot localization failure recovery.
264 0 $c 2010
300 $a 1 online resource (54 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 49-01, page: 4990.
502 $a Thesis (M.A.Sc.) $c University of Windsor (Canada) $d 2010.
504 $a Includes bibliographical references
520 $a Mobile robot localization is one of the most important problems in robotics. Localization is the process of a robot finding out its location given a map of its environment. A number of successful localization solutions have been proposed, among them the well-known and popular Monte Carlo localization method, which is based on particle filters. This thesis proposes a localization approach based on particle filters, using a different way of initializing and resampling of the particles, that reduces the cost of localization. Ultrasonic and light sensors are used in order to perform the experiments. Monte Carlo Localization may fail to localize the robot properly because of the premature convergence of the particles. Using more number of particles increases the computational cost of localization process. Experimental results show that, applying the proposed method robot can successfully localize itself using less number of particles; therefore the cost of localization is decreased.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of Windsor (Canada). $3 1182101
773 0 $t Masters Abstracts International $g 49-01.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR62736 $z click for full text (PQDT)

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