@proceedings{CUr/Lea/2013,
author = "Urdiales Garc{\'i}a, Cristina and Peula Palacios, Jos{\'e} Manuel and Fern{\'a}ndez Carmona, Manuel and Sandoval Hern{\'a}ndez, Francisco",
abstract = "Mobility assistance is of key importance for people with dis-
abilities to remain autonomous in their preferred environments. In severe
cases, assistance can be provided by robotized wheelchairs that can per-
form complex maneuvers and/or correct the user’s commands. User’s ac-
ceptance 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.",
booktitle = "ICCBR 2013, LNAI 7969",
editor = "(Sarah Jane Delany and Santiago Onta{\~n}{\'o}n, Eds.)",
isbn = "9783642390555",
issn = "0302-9743",
pages = "329–342",
publisher = "Springer-Verlag Berlin Heidelberg",
series = "LNAI 7969, pp. 329-342",
title = "{L}earning-{B}ased {A}daptation for {P}ersonalized {M}obility {A}ssistance",
url = "http://link.springer.com/chapter/10.1007%2F978-3-642-39056-2_24#",
year = "2013",
}