UM
Bio-inspired group modeling and analysis for intruder detection in mobile sensor/robotic networks
Fu B.1; Xiao Y.1; Liang X.1; Philip Chen C.L.2
2015
Source PublicationIEEE Transactions on Cybernetics
ISSN21682267
Volume45Issue:1Pages:103-115
AbstractAlthough previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates' social and communication systems, and applying what is learned from them to engineering domains is likely to inspire solutions to a number of problems. This paper presents a novel bio-inspired approach to determine group size by researching and simulating primate society. Group size does matter for both primate society and digital entities. It is difficult to determine how to group mobile sensors/robots that patrol in a large area when many factors are considered such as patrol efficiency, wireless interference, coverage, inter/intragroup communications, etc. This paper presents a simulation-based theoretical study on patrolling strategies for robot groups with the comparison of large and small groups through simulations and theoretical results.
KeywordBio-inspired communication Robot grouping Wireless networks
DOI10.1109/TCYB.2014.2320717
URLView the original
Language英語
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Cited Times [WOS]:15   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.University of Alabama
2.Universidade de Macau
Recommended Citation
GB/T 7714
Fu B.,Xiao Y.,Liang X.,et al. Bio-inspired group modeling and analysis for intruder detection in mobile sensor/robotic networks[J]. IEEE Transactions on Cybernetics,2015,45(1):103-115.
APA Fu B.,Xiao Y.,Liang X.,&Philip Chen C.L..(2015).Bio-inspired group modeling and analysis for intruder detection in mobile sensor/robotic networks.IEEE Transactions on Cybernetics,45(1),103-115.
MLA Fu B.,et al."Bio-inspired group modeling and analysis for intruder detection in mobile sensor/robotic networks".IEEE Transactions on Cybernetics 45.1(2015):103-115.
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