Publication
A quadral-Fuzzy control approach to flight formation by a fleet of unmanned aerial vehicles
| dc.contributor.author | Simões Teixeira, Marco António | |
| dc.contributor.author | Neves Juniór, Flávio | |
| dc.contributor.author | Koubaa, Anis | |
| dc.contributor.author | Ramos de Arruda, Lúcia Valéria | |
| dc.contributor.author | Schneider de Oliveira, André | |
| dc.date.accessioned | 2020-07-28T12:57:03Z | |
| dc.date.available | 2020-07-28T12:57:03Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | This paper addresses the control of a fleet of unmanned aerial systems (UAVs), termed as drones, for flight formation problems. Getting drones to fly in formation is a relevant problem to be solved when cooperative cargo transportation is desired. A general approach for this problem considers the coordination of a fleet of UAVs, by fusing all information coming from several individual sensors posed on each UAVs. However, this approach induces a high cost as every UAV should have its advanced perception system. As an alternative, this paper proposes the use of a single perception system by a fleet composed of several elementary drones (workers) with primitive low-cost sensors and a leader drone carrying a 3D perception source. We propose a Quadral-Fuzzy approach to ensure that all drones fly in formation and will not collide with each other or with environment obstacles. We also develop a new way to compute potential fields based on possibility fuzzy (fuzziness) measure with the focus of avoiding collisions between the drones. The proposed approach encompasses four high-coupled intelligent controllers that respectively control the leader and worker drones' motion and implement obstacle and collision avoidance procedures. Simulation results using a fleet of four aerial drones are presented, showing the potential for solving usual problems to flights in formation, such as dodging obstacles, avoiding collisions between the drones, among others. | pt_PT |
| dc.description.sponsorship | This work was supported in part by the National Counsel of Technological and Scientific Development of Brazil (CNPq), in part by the Coordination for the Improvement of Higher Level People (CAPES), in part by the Brazilian Ministry of Science, Technology, Innovation and Communication (MCTIC), and in part by the Robotics and Internet-of-Things Lab in Prince Sultan University. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1109/ACCESS.2020.2985032 | pt_PT |
| dc.identifier.issn | 2169-3536 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/16137 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Institute of Electrical and Electronics Engineers | pt_PT |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9054999 | pt_PT |
| dc.subject | Unmanned aerial vehicles (UAVs) | pt_PT |
| dc.subject | Multi-agent systems | pt_PT |
| dc.subject | Distance-based formation | pt_PT |
| dc.subject | Flight-formation control | pt_PT |
| dc.subject | Autonomous flight | pt_PT |
| dc.title | A quadral-Fuzzy control approach to flight formation by a fleet of unmanned aerial vehicles | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 64381 | pt_PT |
| oaire.citation.startPage | 64366 | pt_PT |
| oaire.citation.title | IEEE Access | pt_PT |
| oaire.citation.volume | 8 | pt_PT |
| person.familyName | Koubaa | |
| person.givenName | Anis | |
| person.identifier | 989131 | |
| person.identifier.ciencia-id | CA19-2399-D94A | |
| person.identifier.orcid | 0000-0003-3787-7423 | |
| person.identifier.scopus-author-id | 15923354900 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | 0337d7df-5f77-46a4-8269-83d14bd5ea6b | |
| relation.isAuthorOfPublication.latestForDiscovery | 0337d7df-5f77-46a4-8269-83d14bd5ea6b |
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