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Author Mcgill, Kathleen ♦ Taylor, Stephen
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Bayesian filters ♦ Bayesian occupancy mapping ♦ Source localization ♦ Biologically inspired algorithms ♦ Hill-climbing algorithms ♦ Mobile robotic networks ♦ Swarm algorithms
Abstract The problem of time-varying, multisource localization using robotic swarms has received relatively little attention when compared to single-source localization. It involves distinct challenges regarding how to partition the robots during search to ensure that all sources are located in minimal time, how to avoid obstacles and other robots, and how to proceed after each source is found. Unfortunately, no common set of validation problems and reference algorithms has evolved, and there are no general theoretical foundations that guarantee progress, convergence, and termination. This article surveys the current multisource literature from the viewpoint of these central questions.
ISSN 03600300
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-04-01
Publisher Place New York
e-ISSN 15577341
Journal ACM Computing Surveys (CSUR)
Volume Number 43
Issue Number 3
Page Count 25
Starting Page 1
Ending Page 25

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Source: ACM Digital Library