Pub Date : 2020-08-10DOI: 10.1109/ICAS49788.2021.9551119
J. Avigad, Floris van Doorn
We consider a perimeter surveillance problem introduced by Kingston, Beard, and Holt in 2008 and studied by Davis, Humphrey, and Kingston in 2019. In this problem, n drones surveil a finite interval, moving at uniform speed and exchanging information only when they meet another drone. Kingston et al. described a particular online algorithm for coordinating their behavior and asked for an upper bound on how long it can take before the drones are fully synchronized. They divided the algorithm’s behavior into two phases and presented upper bounds on the length of each phase based on conjectured worst-case configurations. Davis et al. presented counterexamples to the conjecture for phase 1. We present sharp upper bounds on phase 2 which show that in this case the conjectured worst case is correct, and we report new lower bounds on phase 1.
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Self-organization is one of the most important features observed in social, economic, ecological and biological systems. Distributed self-organizing systems are able to generate emergent global behaviors through local interactions between individuals without a centralized control. Such systems are supposed to be robust, self-repairable and highly adaptive. However, design of self-organizing systems is very challenging, particularly when the emerged global behaviors are required to be predictable or predictable. This talk introduces a morphogenetic approach to the self-organizing swarm robots using genetic and cellular mechanisms governing the biological morphogenesis. We demonstrate that morphogenetic self-organizing algorithms are able to autonomously generate patterns and surround moving targets without centralized control. Finally, morphogen based methods for self-organization of simplistic robots that do not have localization and orientation capabilities are presented.
{"title":"Morphogenetic Self-Organization of Collective Systems","authors":"Yaochu Jin","doi":"10.1145/1998642.1998644","DOIUrl":"https://doi.org/10.1145/1998642.1998644","url":null,"abstract":"Self-organization is one of the most important features observed in social, economic, ecological and biological systems. Distributed self-organizing systems are able to generate emergent global behaviors through local interactions between individuals without a centralized control. Such systems are supposed to be robust, self-repairable and highly adaptive. However, design of self-organizing systems is very challenging, particularly when the emerged global behaviors are required to be predictable or predictable. This talk introduces a morphogenetic approach to the self-organizing swarm robots using genetic and cellular mechanisms governing the biological morphogenesis. We demonstrate that morphogenetic self-organizing algorithms are able to autonomously generate patterns and surround moving targets without centralized control. Finally, morphogen based methods for self-organization of simplistic robots that do not have localization and orientation capabilities are presented.","PeriodicalId":287105,"journal":{"name":"2021 IEEE International Conference on Autonomous Systems (ICAS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134173266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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