A neurorobotics approach to behaviour selection based on human activity recognition

Autor(es)

Ranieri, Caetano M. ; Moioli, Renan C. ; Vargas, Patricia A. ; Romero, Roseli A. F.

• Tipo de documento: Artigo Científico
• Fonte: COGNITIVE NEURODYNAMIC; v. N/A, p. 20-pg., 2022-09-27.

Resumo

Behaviour selection has been an active research topic for robotics, in particular in the field of human-robot interaction. For a robot to interact autonomously and effectively with humans, the coupling between techniques for human activity recognition and robot behaviour selection is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting an initial neurorobotics model that embeds, in a simulated robot, computational models of parts of the mammalian brain that resembles neurophysiological aspects of the basal ganglia-thalamus-cortex (BG-T-C) circuit, coupled with human activity recognition techniques. A robotics simulation environment was developed for assessing the model, where a mobile robot accomplished tasks by using behaviour selection in accordance with the activity being performed by the inhabitant of an intelligent home. Initial results revealed that the initial neurorobotics model is advantageous, especially considering the coupling between the most accurate activity recognition approaches and the computational models of more complex animals. (AU)

• Processo FAPESP: 18/25902-0 - Aprendizado de máquina para ajudar a encontrar correlatos neurais do Mal de Parkinson
• Beneficiário: Caetano Mazzoni Ranieri
• Modalidade de apoio: Bolsas no Exterior - Estágio de Pesquisa - Doutorado
• Processo FAPESP: 21/10921-2 - Processamento de imagens para detecção e predição de enchentes
• Beneficiário: Caetano Mazzoni Ranieri
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
• Beneficiário: Francisco Louzada Neto
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 17/02377-5 - Aprendizado de Máquina e Aplicações para Robótica em Ambientes Inteligentes
• Beneficiário: Caetano Mazzoni Ranieri
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 17/01687-0 - Arquitetura e aplicações para robótica em ambientes inteligentes
• Beneficiário: Roseli Aparecida Francelin Romero
• Modalidade de apoio: Auxílio à Pesquisa - Regular