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Crane collision modelling using a neural network approach

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Crane collision modelling using a neural network approach

dc.contributor.author	García-Fernández, Ignacio
dc.contributor.author	Martín Guerrero, José David
dc.contributor.author	Pla i Castells, Marta
dc.contributor.author	Soria Olivas, Emilio
dc.contributor.author	Martínez Durá, Rafael J.
dc.contributor.author	Muñoz Marí, Jordi
dc.date.accessioned	2017-09-28T14:22:16Z
dc.date.available	2017-09-28T14:22:16Z
dc.date.issued	2004
dc.identifier.citation	García Fernández, Ignacio Martín Guerrero, José David Pla i Castells, Marta Soria Olivas, Emilio Martínez Durá, Rafael J. Muñoz Marí, Jordi 2004 Crane collision modelling using a neural network approach Expert Systems With Applications 27 3 341 348
dc.identifier.uri	http://hdl.handle.net/10550/61259
dc.description.abstract	The objective of the present work is to find a Collision Detection algorithm to be used in the Virtual Reality crane simulator (UVSim®), developed by the Robotics Institute of the University of Valencia for the Port of Valencia. The method is applicable to box-shaped objects and is based on the relationship between the colliding object positions and their impact points. The tool chosen to solve the problem is a neural network, the multilayer perceptron, which adapts to the characteristics of the problem, namely, non-linearity, a large amount of data, and no a priori knowledge. The results achieved by the neural network are very satisfactory for the case of box-shaped objects. Furthermore, the computational burden is independent from the object positions and how the surfaces are modelled; hence, it is suitable for the real-time requirements of the application and outperforms the computational burden of other classical methods. The model proposed is currently being used and validated in the UVSim Gantry Crane simulator.
dc.language.iso	eng
dc.relation.ispartof	Expert Systems With Applications, 2004, vol. 27, num. 3, p. 341-348
dc.subject	Simulació per ordinador
dc.subject	Xarxes neuronals (Informàtica)
dc.title	Crane collision modelling using a neural network approach
dc.type	journal article	es_ES
dc.date.updated	2017-09-28T14:22:16Z
dc.identifier.doi	10.1016/j.eswa.2004.05.002
dc.identifier.idgrec	013858
dc.rights.accessRights	open access	es_ES