Publication:
Error Reduction in Vision-Based Multirotor Landing System

Simple item page
dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Grupo de Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorLlerena Caña, Juan Pedro
dc.contributor.authorGarcía Herrero, Jesús
dc.contributor.authorMolina López, José Manuel
dc.contributor.funderComunidad de Madrides
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.contributor.funderUniversidad Carlos III de Madrides
dc.date.accessioned2023-07-20T11:27:29Z
dc.date.available2023-07-20T11:27:29Z
dc.date.issued2022-05-10
dc.description.abstractNew applications are continuously appearing with drones as protagonists, but all of them share an essential critical maneuver—landing. New application requirements have led the study of novel landing strategies, in which vision systems have played and continue to play a key role. Generally, the new applications use the control and navigation systems embedded in the aircraft. However, the internal dynamics of these systems, initially focused on other tasks such as the smoothing trajectories between different waypoints, can trigger undesired behaviors. In this paper, we propose a landing system based on monocular vision and navigation information to estimate the helipad global position. In addition, the global estimation system includes a position error correction module by cylinder space transformation and a filtering system with a sliding window. To conclude, the landing system is evaluated with three quality metrics, showing how the proposed correction system together with stationary filtering improves the raw landing system.en
dc.description.sponsorshipThis research was partially funded by public research projects of Spanish Ministry of Science and Innovation, references PID2020-118249RB-C22 and PDC2021-121567-C22—AEI/10.13039/501100011033, and by the Madrid Government (Comunidad de Madrid, Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors, reference EPUC3M17.en
dc.identifier.bibliographicCitationLlerena Caña, J.P.; García Herrero, J.; Molina López, J.M. Error Reduction in Vision-Based Multirotor Landing System. Sensors 2022, 22, 3625.es
dc.identifier.doihttps://doi.org/10.3390/s22103625
dc.identifier.issn1424-3210
dc.identifier.publicationfirstpage3625
dc.identifier.publicationissue10
dc.identifier.publicationlastpage3650
dc.identifier.publicationtitleSensorsen
dc.identifier.publicationvolume22
dc.identifier.urihttps://hdl.handle.net/10016/37920
dc.identifier.uxxiAR/0000030660
dc.language.isoengen
dc.publisherMDPIen
dc.relation.projectIDComunidad de Madrid.es
dc.relation.projectIDGobierno de España. PID2020-118249RB-C22es
dc.relation.projectIDGobierno de España. PDC2021-121567-C22es
dc.rights© 2022 by the authorsen
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherUAVen
dc.subject.otherautonomous landingen
dc.subject.otherfilteringen
dc.subject.othercomputer visione
dc.subject.otherhelipad contexten
dc.subject.otherglobal positionen
dc.subject.othernavigation systemen
dc.subject.othersitlen
dc.titleError Reduction in Vision-Based Multirotor Landing Systemen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
error_S_2022.pdf
Size:
6.63 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
DI - GIAA - Artículos de Revistas