Loading…

Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence

This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fa...

Full description

Saved in:
Bibliographic Details
Published in:IEEE consumer electronics magazine 2020-03, Vol.9 (2), p.52-56
Main Authors: Chen, Bo-Wei, Rho, Seungmin
Format: Magazinearticle
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663
cites cdi_FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663
container_end_page 56
container_issue 2
container_start_page 52
container_title IEEE consumer electronics magazine
container_volume 9
creator Chen, Bo-Wei
Rho, Seungmin
description This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fail to work due to natural disasters. To be rapidly deployed, lightweight drones with multirotors that provide stability are used as mobile stations. An autonomous learning approach, "self-organizing maps (SOMs)," which can automatically and adaptively coordinate a large array of autonomous drones-self-organizing UAV array-based on requests from end users (EUs) is embedded inside the array. The size and the topology of a UAV array can be dynamically changed in response to various terrains and relocation of EUs. Moreover, with swarm intelligence, the UAV array is capable of reconfiguring its planar topology into a hierarchical one. Such a hierarchical topology divides the entire UAV array into subarrays and creates isolated heterogeneous networks. Thus, the UAV array can cope with diverse situations across geographical barriers by forming a flying ad hoc network.
doi_str_mv 10.1109/MCE.2019.2954051
format magazinearticle
fullrecord <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_proquest_miscellaneous_2350155698</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>8977811</ieee_id><sourcerecordid>2350155698</sourcerecordid><originalsourceid>FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663</originalsourceid><addsrcrecordid>eNo9kM1LAzEQxYMoWGrvgpccvWzNxyabHJdatVDpwVa8hWw6qSv7UZMtUv96t7Z0LjMD7w1vfgjdUjKmlOiH18l0zAjVY6ZFSgS9QANGJUsYE_LyPKfqGo1i_CJ9SUIZ1QP0ke-6tmnrdhfx0rqudLbCj7Ct2n0NTYdbj7tPwKv8Hech2D1exbLZ4DeofLIIG9uUv__7jw01njUdVFW5gcbBDbrytoowOvUhWj1Nl5OXZL54nk3yeeKYll1SAAjQOnOcSSBewVopnmqt1o7LQnjwWUELVfiUykJlXBOdZVoyTqkDLSUfovvj3W1ov3cQO1OX0fUxbAP9U4ZxQagQUqteSo5SF9oYA3izDWVtw95QYg4cTc_RHDiaE8fecne0lABwlqs-g6KU_wHyU23O</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>magazinearticle</recordtype><pqid>2350155698</pqid></control><display><type>magazinearticle</type><title>Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Chen, Bo-Wei ; Rho, Seungmin</creator><creatorcontrib>Chen, Bo-Wei ; Rho, Seungmin</creatorcontrib><description>This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fail to work due to natural disasters. To be rapidly deployed, lightweight drones with multirotors that provide stability are used as mobile stations. An autonomous learning approach, "self-organizing maps (SOMs)," which can automatically and adaptively coordinate a large array of autonomous drones-self-organizing UAV array-based on requests from end users (EUs) is embedded inside the array. The size and the topology of a UAV array can be dynamically changed in response to various terrains and relocation of EUs. Moreover, with swarm intelligence, the UAV array is capable of reconfiguring its planar topology into a hierarchical one. Such a hierarchical topology divides the entire UAV array into subarrays and creates isolated heterogeneous networks. Thus, the UAV array can cope with diverse situations across geographical barriers by forming a flying ad hoc network.</description><identifier>ISSN: 2162-2248</identifier><identifier>EISSN: 2162-2256</identifier><identifier>DOI: 10.1109/MCE.2019.2954051</identifier><identifier>CODEN: ICEMCQ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Ad hoc networks ; Arrays ; Drone aircraft ; Drones ; End users ; Military strategy ; Mobile computing ; Natural disasters ; Neurons ; Particle swarm optimization ; Relocation ; Self organizing maps ; Stations ; Swarm intelligence ; Topology ; Unmanned aerial vehicles</subject><ispartof>IEEE consumer electronics magazine, 2020-03, Vol.9 (2), p.52-56</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663</citedby><cites>FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663</cites><orcidid>0000-0001-6526-9017 ; 0000-0003-1936-6785</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8977811$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>780,784,27925,54796</link.rule.ids></links><search><creatorcontrib>Chen, Bo-Wei</creatorcontrib><creatorcontrib>Rho, Seungmin</creatorcontrib><title>Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence</title><title>IEEE consumer electronics magazine</title><addtitle>MCE</addtitle><description>This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fail to work due to natural disasters. To be rapidly deployed, lightweight drones with multirotors that provide stability are used as mobile stations. An autonomous learning approach, "self-organizing maps (SOMs)," which can automatically and adaptively coordinate a large array of autonomous drones-self-organizing UAV array-based on requests from end users (EUs) is embedded inside the array. The size and the topology of a UAV array can be dynamically changed in response to various terrains and relocation of EUs. Moreover, with swarm intelligence, the UAV array is capable of reconfiguring its planar topology into a hierarchical one. Such a hierarchical topology divides the entire UAV array into subarrays and creates isolated heterogeneous networks. Thus, the UAV array can cope with diverse situations across geographical barriers by forming a flying ad hoc network.</description><subject>Ad hoc networks</subject><subject>Arrays</subject><subject>Drone aircraft</subject><subject>Drones</subject><subject>End users</subject><subject>Military strategy</subject><subject>Mobile computing</subject><subject>Natural disasters</subject><subject>Neurons</subject><subject>Particle swarm optimization</subject><subject>Relocation</subject><subject>Self organizing maps</subject><subject>Stations</subject><subject>Swarm intelligence</subject><subject>Topology</subject><subject>Unmanned aerial vehicles</subject><issn>2162-2248</issn><issn>2162-2256</issn><fulltext>true</fulltext><rsrctype>magazinearticle</rsrctype><creationdate>2020</creationdate><recordtype>magazinearticle</recordtype><recordid>eNo9kM1LAzEQxYMoWGrvgpccvWzNxyabHJdatVDpwVa8hWw6qSv7UZMtUv96t7Z0LjMD7w1vfgjdUjKmlOiH18l0zAjVY6ZFSgS9QANGJUsYE_LyPKfqGo1i_CJ9SUIZ1QP0ke-6tmnrdhfx0rqudLbCj7Ct2n0NTYdbj7tPwKv8Hech2D1exbLZ4DeofLIIG9uUv__7jw01njUdVFW5gcbBDbrytoowOvUhWj1Nl5OXZL54nk3yeeKYll1SAAjQOnOcSSBewVopnmqt1o7LQnjwWUELVfiUykJlXBOdZVoyTqkDLSUfovvj3W1ov3cQO1OX0fUxbAP9U4ZxQagQUqteSo5SF9oYA3izDWVtw95QYg4cTc_RHDiaE8fecne0lABwlqs-g6KU_wHyU23O</recordid><startdate>20200301</startdate><enddate>20200301</enddate><creator>Chen, Bo-Wei</creator><creator>Rho, Seungmin</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0001-6526-9017</orcidid><orcidid>https://orcid.org/0000-0003-1936-6785</orcidid></search><sort><creationdate>20200301</creationdate><title>Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence</title><author>Chen, Bo-Wei ; Rho, Seungmin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663</frbrgroupid><rsrctype>magazinearticle</rsrctype><prefilter>magazinearticle</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Ad hoc networks</topic><topic>Arrays</topic><topic>Drone aircraft</topic><topic>Drones</topic><topic>End users</topic><topic>Military strategy</topic><topic>Mobile computing</topic><topic>Natural disasters</topic><topic>Neurons</topic><topic>Particle swarm optimization</topic><topic>Relocation</topic><topic>Self organizing maps</topic><topic>Stations</topic><topic>Swarm intelligence</topic><topic>Topology</topic><topic>Unmanned aerial vehicles</topic><toplevel>online_resources</toplevel><creatorcontrib>Chen, Bo-Wei</creatorcontrib><creatorcontrib>Rho, Seungmin</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE consumer electronics magazine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Bo-Wei</au><au>Rho, Seungmin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence</atitle><jtitle>IEEE consumer electronics magazine</jtitle><stitle>MCE</stitle><date>2020-03-01</date><risdate>2020</risdate><volume>9</volume><issue>2</issue><spage>52</spage><epage>56</epage><pages>52-56</pages><issn>2162-2248</issn><eissn>2162-2256</eissn><coden>ICEMCQ</coden><abstract>This article describes how swarm intelligence can be applied to an array of autonomous unmanned aerial vehicles (UAVs) for strategic deployment. In emergency or disaster-stricken areas, telecommunications and geospatial surveillance are strictly critical for situational control. Base stations may fail to work due to natural disasters. To be rapidly deployed, lightweight drones with multirotors that provide stability are used as mobile stations. An autonomous learning approach, "self-organizing maps (SOMs)," which can automatically and adaptively coordinate a large array of autonomous drones-self-organizing UAV array-based on requests from end users (EUs) is embedded inside the array. The size and the topology of a UAV array can be dynamically changed in response to various terrains and relocation of EUs. Moreover, with swarm intelligence, the UAV array is capable of reconfiguring its planar topology into a hierarchical one. Such a hierarchical topology divides the entire UAV array into subarrays and creates isolated heterogeneous networks. Thus, the UAV array can cope with diverse situations across geographical barriers by forming a flying ad hoc network.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/MCE.2019.2954051</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0001-6526-9017</orcidid><orcidid>https://orcid.org/0000-0003-1936-6785</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 2162-2248
ispartof IEEE consumer electronics magazine, 2020-03, Vol.9 (2), p.52-56
issn 2162-2248
2162-2256
language eng
recordid cdi_proquest_miscellaneous_2350155698
source IEEE Electronic Library (IEL) Journals
subjects Ad hoc networks
Arrays
Drone aircraft
Drones
End users
Military strategy
Mobile computing
Natural disasters
Neurons
Particle swarm optimization
Relocation
Self organizing maps
Stations
Swarm intelligence
Topology
Unmanned aerial vehicles
title Autonomous Tactical Deployment of the UAV Array Using Self-Organizing Swarm Intelligence
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-02T19%3A15%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Autonomous%20Tactical%20Deployment%20of%20the%20UAV%20Array%20Using%20Self-Organizing%20Swarm%20Intelligence&rft.jtitle=IEEE%20consumer%20electronics%20magazine&rft.au=Chen,%20Bo-Wei&rft.date=2020-03-01&rft.volume=9&rft.issue=2&rft.spage=52&rft.epage=56&rft.pages=52-56&rft.issn=2162-2248&rft.eissn=2162-2256&rft.coden=ICEMCQ&rft_id=info:doi/10.1109/MCE.2019.2954051&rft_dat=%3Cproquest_ieee_%3E2350155698%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c296t-bee5e997c326e0f8ed8834998dc36b5fef7b1b8bf416b87390977962311ce9663%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2350155698&rft_id=info:pmid/&rft_ieee_id=8977811&rfr_iscdi=true