國立虎尾科技大學 |

An improved approach for multi-robot localization.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	An improved approach for multi-robot localization./
作者:	Su, Huaicheng.
面頁冊數:	1 online resource (100 pages)
附註:	Source: Masters Abstracts International, Volume: 47-04, page: 2241.
Contained By:	Masters Abstracts International47-04.
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9780494470367

An improved approach for multi-robot localization.
Su, Huaicheng.

An improved approach for multi-robot localization. - 1 online resource (100 pages)

Source: Masters Abstracts International, Volume: 47-04, page: 2241.

Thesis (M.Sc.)--University of Windsor (Canada), 2008.

Includes bibliographical references

Cooperative multi-robot localization techniques use sensor measurements to estimate poses (locations, orientations) of robots relative to a given map of the environment. Existing approaches update a robot's pose instantly whenever it detects another robot. However, such instant update may not be always necessary and effective, since both robots' pose estimates could be highly uncertain at the time of the detection. In this thesis, we develop a new information exchange mechanism to collaborative multi-robot localization. We also propose a new scheme to calculate how much information is contained in a robot's belief by using entropy. Instead of updating beliefs whenever detection occurs, our approach first compares the beliefs of the robots which are involved in the detection, and then decide whether the information exchange is necessary. Therefore, it avoids unnecessary information exchange whenever one robot perceives another robot. On the other hand, this approach does allow information exchange between detecting robots and such information exchange always contributes positively to the localization process, hence, improving the effectiveness and efficiency of multi-robot localization. The technique has been implemented and tested using two mobile robots as well as simulations. The results indicate significant improvements in localization speed and accuracy when compared to the single mobile robot localization.

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

Mode of access: World Wide Web

ISBN: 9780494470367Subjects--Topical Terms:

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

554714
Electronic books.

An improved approach for multi-robot localization.
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245 1 3 $a An improved approach for multi-robot localization.
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500 $a Source: Masters Abstracts International, Volume: 47-04, page: 2241.
502 $a Thesis (M.Sc.)--University of Windsor (Canada), 2008.
504 $a Includes bibliographical references
520 $a Cooperative multi-robot localization techniques use sensor measurements to estimate poses (locations, orientations) of robots relative to a given map of the environment. Existing approaches update a robot's pose instantly whenever it detects another robot. However, such instant update may not be always necessary and effective, since both robots' pose estimates could be highly uncertain at the time of the detection. In this thesis, we develop a new information exchange mechanism to collaborative multi-robot localization. We also propose a new scheme to calculate how much information is contained in a robot's belief by using entropy. Instead of updating beliefs whenever detection occurs, our approach first compares the beliefs of the robots which are involved in the detection, and then decide whether the information exchange is necessary. Therefore, it avoids unnecessary information exchange whenever one robot perceives another robot. On the other hand, this approach does allow information exchange between detecting robots and such information exchange always contributes positively to the localization process, hence, improving the effectiveness and efficiency of multi-robot localization. The technique has been implemented and tested using two mobile robots as well as simulations. The results indicate significant improvements in localization speed and accuracy when compared to the single mobile robot localization.
520 $a Keywords. multi-robot, localization, Monte Carlo, belief, entropy, density estimation.
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
650 4 $a Robotics. $3 561941
655 7 $a Electronic books. $2 local $3 554714
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