dc.creator | Ramón Soria, Pablo | es |
dc.creator | Bevec, Robert | es |
dc.creator | Arrue Ullés, Begoña C. | es |
dc.creator | Ude, Aleš | es |
dc.creator | Ollero Baturone, Aníbal | es |
dc.date.accessioned | 2016-10-11T09:48:00Z | |
dc.date.available | 2016-10-11T09:48:00Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Ramón Soria, P., Bevec, R., Arrue Ulles, B.C., Ude, A. y Ollero Baturone, A. (2016). Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors. Sensors, 16 (700) | |
dc.identifier.issn | 1424-8220 | es |
dc.identifier.uri | http://hdl.handle.net/11441/47371 | |
dc.description.abstract | Giving unmanned aerial vehicles (UAVs) the possibility to manipulate objects vastly
extends the range of possible applications. This applies to rotary wing UAVs in particular, where their
capability of hovering enables a suitable position for in-flight manipulation. Their manipulation skills
must be suitable for primarily natural, partially known environments, where UAVs mostly operate.
We have developed an on-board object extraction method that calculates information necessary for
autonomous grasping of objects, without the need to provide the model of the object’s shape. A local
map of the work-zone is generated using depth information, where object candidates are extracted
by detecting areas different to our floor model. Their image projections are then evaluated using
support vector machine (SVM) classification to recognize specific objects or reject bad candidates.
Our method builds a sparse cloud representation of each object and calculates the object’s centroid
and the dominant axis. This information is then passed to a grasping module. Our method works
under the assumption that objects are static and not clustered, have visual features and the floor
shape of the work-zone area is known. We used low cost cameras for creating depth information that
cause noisy point clouds, but our method has proved robust enough to process this data and return
accurate results. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad AEROMAIN (DPI2014-59383-C2-1-R) | es |
dc.description.sponsorship | Unión Europea AEROARMS (SI-1439/2015) | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Sensors, 16 (700) | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | UAV | es |
dc.subject | Object detection | es |
dc.subject | Object recognition | es |
dc.subject | SVM | es |
dc.subject | Manipulation | es |
dc.title | Extracting Objects for Aerial Manipulation on UAVs Using Low Cost Stereo Sensors | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática | es |
dc.relation.projectID | SI-1439/2015 | es |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/DPI2014-59383-C2-1-R | es |
dc.relation.publisherversion | http://www.mdpi.com/1424-8220/16/5/700 | es |
dc.identifier.doi | 10.3390/s16050700 | es |
idus.format.extent | 19 p. | es |
dc.journaltitle | Sensors | es |
dc.publication.volumen | 16 | es |
dc.publication.issue | 700 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/47371 | |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | |
dc.contributor.funder | European Union (UE) | |