{"refrec":{"BRefID":323301,"RR":"<b>Zhang, R.; Holvoet, T.; Song, B.; Pei, Y.</b> (2018). UAVs versus pirates: a pheromone-based swarm monitoring method, <b><i>in</i></b>: <i>2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)\r\n.</i> pp. 2253-2258","BEntID":316773,"PublicFlag":1,"CheckedFlag":1,"wosflag":0,"vabbflag":0,"RefStringPartII":", <b><i>in</i></b>: <i>2018 IEEE International Conference on Robotics and Biomimetics (ROBIO).</i> pp. 2253-2258","DocTypID":17,"DocType":"Book chapters","MarineFlag":1,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Zhang, R.; Holvoet, T.; Song, B.; Pei, Y.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Zhang, R. <i>et al.</i>","Englishabstract":"As piracy presents great threats to maritime security, unmanned aerial vehicle (UAV) swarm monitoring is becoming an attractive countermeasure. Conventional sweep monitoring method provides balanced coverage but cannot adapt to variable situations, such as the return of IJAN's for refueling. This paper proposes a pheromone-based method for IJAV swarm anti-piracy monitoring. In this method, the environment is modeled by a pheromone map, and the motion of IJAN's is guided by the strength of pheromones. A ship-centered convening mechanism is proposed to increase the chance of finding pirates by taking the interactions between pirates and merchant ships into account. A prediction-reservation mechanism is proposed to improve the deficiencies of the implicit intention propagation mechanism when the ship-centered convening mechanism is used. Simulation experiments are conducted to study the effectiveness of the proposed method. Results show that the proposed method reduces the success rate of pirate attack by 8% at most compared to the sweep method, and that the prediction-reservation mechanism performs better than the implicit intention propagation mechanism, especially with large number of IJAVs.","AbstractOtherLang":null,"BibLvlCode":"AM","StandardTitle":"UAVs versus pirates: a pheromone-based swarm monitoring method","OrigTitleLangCode":"en","OrigTitleLangCodeExtended":"eng","OrigTitleLangID":15,"DateLastModified":{"date":"2024-12-10 01:33:17.368041","timezone_type":1,"timezone":"+01:00"},"UserAccessRight":null,"UserAccID":null,"AuthorKeywords":null,"OtherDescriptors":null,"Notes":null,"AnaPub":2018,"MonPub":null,"DateUpdate":"2020-04-27","DateCreate":"2020-04-07","SecASFANote":null,"ConfID":null,"PeerRev":0,"VlizCoreFlag":1,"WoScode":"WOS:000468772200354","VABBcode":null,"OpenAcc":0},"refs":null,"anarec":{"AnaID":323301,"PubliDate":2018,"Pagination":"2253-2258","XtraPublOfAnaID":null,"ISBN":"978-1-7281-0377-8","Volume":null,"Issue":null,"BRefMon":323616,"BRefMonRR":"(2018). 2018 IEEE International Conference on Robotics and Biomimetics (ROBIO)\r\n. 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