RT Journal Article
T1 Case-based reasoning emulation of persons for wheelchair navigation.
A1 Peula Palacios, José Manuel
A1 Urdiales-García, Amalia Cristina
A1 Herrero-Reder, Ignacio
A1 Fernández-Carmona, Manuel
A1 Sandoval-Hernández, Francisco
K1 Sillas de ruedas
K1 Inteligencia artificial - Aplicaciones médicas
AB Our approach is based on extracting meaningful data from real users driving a power wheelchair autonomously. This data is then used to train a case-based reasoning (CBR) system that captures the specifics of the driver via learning. The resulting case-base is then used to emulate the driving behavior of that specific person in more complex situations or when a new assistive algorithm needs to be tested. CBR returns user's motion commands appropriate for each specific situation to add the human component to shared control systems.
PB Elsevier
YR 2012
FD 2012
LK https://hdl.handle.net/10630/34269
UL https://hdl.handle.net/10630/34269
LA eng
NO https://v2.sherpa.ac.uk/id/publication/12586
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026