Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/30287
COMPARTIR / EXPORTAR:
SHARE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Ruiz de Angulo, Vicente | - |
dc.contributor.author | Cortés, Juan | - |
dc.contributor.author | Simeon, Thierry | - |
dc.date.accessioned | 2010-12-17T06:53:00Z | - |
dc.date.available | 2010-12-17T06:53:00Z | - |
dc.date.issued | 2005 | - |
dc.identifier.citation | 1st Robotics: Science and Systems Conference: 141-148 (2005) | - |
dc.identifier.isbn | 9780262701143 | - |
dc.identifier.uri | http://hdl.handle.net/10261/30287 | - |
dc.description | Robotics: Science and Systems Conference (RSS), 2005, Cambridge (EE.UU.) | - |
dc.description.abstract | This paper describes an efficient approach to (self) collision detection and distance computations for complex articulated mechanisms such as molecular chains. The proposed algorithm called BioCD is particularly designed for sampling-based motion planning on molecular models described by long kinematic chains possibly including cycles. The algorithm con s that the kinematic chain is structured into a number of rigid groups articulated by preselected degrees of freedom. This structuration is exploited by a two-level spatially-adapted hierarchy. The proposed algorithm is not limited to particular kinematic topologies and allows good collision detection times. BioCD is also tailored to deal with the particularities imposed by the molecular context on collision detection. Experimental results show the effectiveness of the proposed approach which is able to process thousands of (self) collision tests per second on flexible protein models with up to hundreds of degrees of freedom. | - |
dc.description.sponsorship | This work was supported by the project 'Planificador de trayectorias para sistemas robotizados de arquitectura arbitraria' (J-00930). | - |
dc.language.iso | eng | - |
dc.publisher | Massachusetts Institute of Technology | - |
dc.rights | openAccess | - |
dc.subject | Collision detection | - |
dc.subject | Biochemistry | - |
dc.subject | Proteins | - |
dc.subject | Automation: Robots | - |
dc.subject | Robots | - |
dc.subject | Robotics | - |
dc.title | BioCD : An efficient algorithm for self-collision and distance computation between highly articulated molecular models | - |
dc.type | comunicación de congreso | - |
dc.description.peerreviewed | Peer Reviewed | - |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | es_ES |
item.openairetype | comunicación de congreso | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
Aparece en las colecciones: | (IRII) Comunicaciones congresos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
doc1.pdf | 1,54 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
Page view(s)
302
checked on 26-mar-2024
Download(s)
197
checked on 26-mar-2024
Google ScholarTM
Check
Altmetric
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.