Mostrar el registro sencillo del ítem

dc.contributor.authorUrdiales, Cristina 
dc.contributor.authorPeula-Garcia, Jose Manuel 
dc.contributor.authorFernández-Carmona, Manuel
dc.contributor.authorSandoval, Francisco
dc.date.accessioned2013-09-13T10:32:40Z
dc.date.available2013-09-13T10:32:40Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10630/5712
dc.description.abstractMobility assistance is of key importance for people with disabilities to remain autonomous in their preferred environments. In severe cases, assistance can be provided by robotized wheelchairs that can perform complex maneuvers and/or correct the user’s commands. User’s acceptance is of key importance, as some users do not like their commands to be modified. This work presents a solution to improve acceptance. It consists of making the robot learn how the user drives so corrections will not be so noticeable to the user. Case Based Reasoning (CBR) is used to acquire a user’s driving model reactive level. Experiments with volunteers at Fondazione Santa Lucia (FSL) have proven that, indeed, this customized approach at assistance increases acceptance by the user.es_ES
dc.description.sponsorshipThis work has been partially supported by the Spanish Ministerio de Educacion y Ciencia (MEC), Project TEC2011-29106-C02-01. The authors would like to thank Santa Lucia Hospedale and all volunteers for their kind cooperation and Sauer Medica for providing the power wheelchair.es_ES
dc.language.isoenges_ES
dc.publisherSpringer-Verlages_ES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectRobóticaes_ES
dc.subject.otherRoboticses_ES
dc.subject.otherLearninges_ES
dc.subject.otherAssistive technologieses_ES
dc.subject.otherCBRes_ES
dc.titleLearning-Based Adaptation for Personalized Mobility Assistancees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. de Telecomunicaciónes_ES


Ficheros en el ítem

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem