Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10637/10484
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.otherUCH. Departamento de Matemáticas, Física y Ciencias Tecnológicas-
dc.contributor.otherProducción Científica UCH 2018-
dc.creatorMontés Sánchez, Nicolás-
dc.creatorHilario Pérez, Lucía-
dc.creatorNadal Soriano, Enrique-
dc.creatorMora Aguilar, Marta Covadonga-
dc.creatorFalcó Montesinos, Antonio-
dc.creatorChinesta, Francisco-
dc.creatorDuval, Jean Louis-
dc.date2018-
dc.date.accessioned2019-06-29T04:01:34Z-
dc.date.available2019-06-29T04:01:34Z-
dc.date.issued2018-04-27-
dc.identifier.citationMontés, N., Hilario, L., Nadal, E., Mora, MC., Falcó, A., Chinesta, F. et al. (2018). PGD Variational vademecum for robot motion planning : a dynamic obstacle case. ScienceOpen Posters. DOI: https://doi.org/10.14293/P2199-8442.1.SOP-MATH.OKPFPG.v1-
dc.identifier.urihttp://hdl.handle.net/10637/10484-
dc.descriptionEste póster (comunicación) se encuentra disponible en la siguiente URL: https://www.scienceopen.com/document?vid=b193419e-7f0e-43db-a871-368a05ec6131-
dc.description.abstractA fundamental robotics task is to plan collision-free motions for complex bodies from a start to a goal position among a set of static and dynamic obstacles. This problem is well known in the literature as motion planning (or the piano mover's problem). The complexity of the problem has motivated many works in the field of robot path planning. One of the most popular algorithms is the Artificial Potential Field technique (APF). This method defines an artificial potential field in the configuration space (C-space) that produces a robot path from a start to a goal position. This technique is very fast for RT applications. However, the robot could be trapped in a deadlock (local minima of the potential function). The solution of this problem lies in the use of harmonic functions in the generation of the potential field, which satisfy the Laplace equation. Unfortunately, this technique requires a numerical simulation in a discrete mesh, making useless for RT applications. In our previous work, it was presented for the first time, the Proper Generalized Decomposition method to solve the motion planning problem. In that work, the PGD was designed just for static obstacles and computed as a vademecum for all Start and Goal combinations. This work demonstrates that the PGD could be a solution for the motion planning problem. However, in a realistic scenario, it is necessary to take into account more parameters like for instance, dynamic obstacles. The goal of the present paper is to introduce a diffusion term into the Laplace equation in order to take into account dynamic obstacles as an extra parameter. Both cases, isotropic and non-isotropic cases are into account in order to generalize the solution.-
dc.formatapplication/pdf-
dc.language.isoes-
dc.language.isoen-
dc.publisherScienceOpen-
dc.relation.ispartofScienceOpen Posters. Burlington (Massachusetts, Estados Unidos de América) : ScienceOpen.-
dc.rightshttp://creativecommons.org/licenses/by/4.0/deed.es-
dc.subjectRobótica - Modelos matemáticos.-
dc.subjectDescomposición (Matemáticas)-
dc.subjectRobotics - Mathematical models.-
dc.subjectMétodos de simulación.-
dc.subjectSimulation methods.-
dc.subjectDecomposition (Mathematics)-
dc.titlePGD Variational vademecum for robot motion planning : a dynamic obstacle case-
dc.typeComunicación-
dc.identifier.doihttps://doi.org/10.14293/P2199-8442.1.SOP-MATH.OKPFPG.v1-
dc.centroUniversidad Cardenal Herrera-CEU-
Aparece en las colecciones: Dpto. Matemáticas, Física y Ciencias Tecnológicas




Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.