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오현동

Oh, Hyondong
Autonomous Systems Lab.
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dc.citation.endPage 100 -
dc.citation.startPage 83 -
dc.citation.title ROBOTICS AND AUTONOMOUS SYSTEMS -
dc.citation.volume 91 -
dc.contributor.author Oh, Hyondong -
dc.contributor.author Ramezan Shirazi, Ataollah -
dc.contributor.author Sun, Chaoli -
dc.contributor.author Jin, Yaochu -
dc.date.accessioned 2023-12-21T22:16:22Z -
dc.date.available 2023-12-21T22:16:22Z -
dc.date.created 2017-03-24 -
dc.date.issued 2017-05 -
dc.description.abstract Self-organised emergent patterns can be widely seen in natural and man-made complex systems generated by interactions among local components without external or global control. This paper presents a survey of recent research advances in self-organising pattern formation in mobile multi-robot (or swarm robotic) systems. Relevant pattern formation methods are reviewed with a special focus on biologically-inspired self-organising approaches inspired from macroscopic collective behaviours or microscopic multicellular developing mechanisms. As the ultimate goal of this review is to provide insight into pattern formation using real robots, limitations and considerations on dealing with a large number of robots are discussed. In addition, guided self-organisation is also discussed as a design strategy where the swarm robotic system may be endowed with local rules for generating desired global patterns. -
dc.identifier.bibliographicCitation ROBOTICS AND AUTONOMOUS SYSTEMS, v.91, pp.83 - 100 -
dc.identifier.doi 10.1016/j.robot.2016.12.006 -
dc.identifier.issn 0921-8890 -
dc.identifier.scopusid 2-s2.0-85014992140 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/21669 -
dc.identifier.url http://www.sciencedirect.com/science/article/pii/S0921889016300185 -
dc.identifier.wosid 000396949800008 -
dc.language 영어 -
dc.publisher ELSEVIER SCIENCE BV -
dc.title Bio-inspired self-organising multi-robot pattern formation: A review -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Automation & Control Systems; Computer Science, Artificial Intelligence; Robotics -
dc.relation.journalResearchArea Automation & Control Systems; Computer Science; Robotics -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Multi-robot systems -
dc.subject.keywordAuthor Bio-inspired approaches -
dc.subject.keywordAuthor Pattern formation -
dc.subject.keywordAuthor Self-organising systems -
dc.subject.keywordAuthor Swarm robotics -
dc.subject.keywordPlus COHERENT STRUCTURES -
dc.subject.keywordPlus STANDOFF TRACKING -
dc.subject.keywordPlus GENE NETWORKS -
dc.subject.keywordPlus MOBILE ROBOTS -
dc.subject.keywordPlus SHAPE CONTROL -
dc.subject.keywordPlus SWARM -
dc.subject.keywordPlus ORGANIZATION -
dc.subject.keywordPlus MORPHOGENESIS -
dc.subject.keywordPlus COMMUNICATION -
dc.subject.keywordPlus COORDINATION -

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