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A human-in-the-loop approach for enhancing mobile robot navigation in presence of obstacles not detected by the sensory set.
Ferracuti, Francesco; Freddi, Alessandro; Iarlori, Sabrina; Monteriù, Andrea; Omer, Karameldeen Ibrahim Mohamed; Porcaro, Camillo.
Afiliación
  • Ferracuti F; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
  • Freddi A; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
  • Iarlori S; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
  • Monteriù A; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
  • Omer KIM; Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
  • Porcaro C; Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy.
Front Robot AI ; 9: 909971, 2022.
Article en En | MEDLINE | ID: mdl-36523445
Human-in-the-loop approaches can greatly enhance the human-robot interaction by making the user an active part of the control loop, who can provide a feedback to the robot in order to augment its capabilities. Such feedback becomes even more important in all those situations where safety is of utmost concern, such as in assistive robotics. This study aims to realize a human-in-the-loop approach, where the human can provide a feedback to a specific robot, namely, a smart wheelchair, to augment its artificial sensory set, extending and improving its capabilities to detect and avoid obstacles. The feedback is provided by both a keyboard and a brain-computer interface: with this scope, the work has also included a protocol design phase to elicit and evoke human brain event-related potentials. The whole architecture has been validated within a simulated robotic environment, with electroencephalography signals acquired from different test subjects.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Robot AI Año: 2022 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Front Robot AI Año: 2022 Tipo del documento: Article País de afiliación: Italia