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Building a behaviour architecture: An approach for promoting human-robot interaction

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Detalhes bibliográficos
Resumo:Human distraction behaviour is a paramount subject to take into account. Several woks in the literature try to tackle this topic mostly in the automotive industry. Following this trend, the present work proposes a system to detect the patterns of distraction/attention during an interaction activity between a human and a robot. The goal is to analyse selected patterns of distraction, such as eye gaze, head pose, blinking rate, among others, and adapting the robot behaviour, consequently promoting a more fluid interaction. A behavioural state machine that takes into account the engagement and the performance of the user in the activity is proposed.
Autores principais:Amaro, Bruno
Outros Autores:Silva, Vinicius Corrêa Alves; Soares, Filomena; Esteves, João Sena
Assunto:Human–computer interaction Human–robot interaction Machine learning Patterns of attention ZECA robot
Ano:2019
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Human distraction behaviour is a paramount subject to take into account. Several woks in the literature try to tackle this topic mostly in the automotive industry. Following this trend, the present work proposes a system to detect the patterns of distraction/attention during an interaction activity between a human and a robot. The goal is to analyse selected patterns of distraction, such as eye gaze, head pose, blinking rate, among others, and adapting the robot behaviour, consequently promoting a more fluid interaction. A behavioural state machine that takes into account the engagement and the performance of the user in the activity is proposed.