Assistive robots operate in complex environments and in presence of human beings, as such they are influenced by several factors which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions or algorithmic errors represent just few examples. When the safety of the user must be guaranteed, a possible solution is to rely on a human-supervised approach. The proposed work presents a smart wheelchair, i.e. an electric powered wheelchair with semiautonomous navigation capabilities, whose user is equipped with a Brain Computer Interface. During the wheelchair navigation, possible problems (e.g. obstacles) along the trajectory cause the generation of error-related potentials signals when noticed by the user. These signals are captured by the interface and are used to provide a feedback to the navigation task, in order to preserve safety and avoiding possible navigation issues.
ErrP Signals Detection for Safe Navigation of a Smart Wheelchair / Ciabattoni, L.; Ferracuti, F.; Freddi, A.; Iarlori, S.; Longhi, S.; Monteriu, A.. - (2019), pp. 269-272. (Intervento presentato al convegno 23rd IEEE International Symposium on Consumer Technologies, ISCT 2019 tenutosi a Ancona, Italy nel 2019) [10.1109/ISCE.2019.8900993].
ErrP Signals Detection for Safe Navigation of a Smart Wheelchair
Ciabattoni L.;Ferracuti F.;Freddi A.;Iarlori S.;Longhi S.;Monteriu A.
2019-01-01
Abstract
Assistive robots operate in complex environments and in presence of human beings, as such they are influenced by several factors which may lead to undesired outcomes: wrong sensor readings, unexpected environmental conditions or algorithmic errors represent just few examples. When the safety of the user must be guaranteed, a possible solution is to rely on a human-supervised approach. The proposed work presents a smart wheelchair, i.e. an electric powered wheelchair with semiautonomous navigation capabilities, whose user is equipped with a Brain Computer Interface. During the wheelchair navigation, possible problems (e.g. obstacles) along the trajectory cause the generation of error-related potentials signals when noticed by the user. These signals are captured by the interface and are used to provide a feedback to the navigation task, in order to preserve safety and avoiding possible navigation issues.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
