A neural integrator model for planning and value-based decision making of a robotics assistant

Modern manufacturing and assembly environments are characterized by a high variability in the built process which challenges human–robot cooperation. To reduce the cognitive workload of the operator, the robot should not only be able to learn from experience but also to plan and decide autonomously....

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Detalhes bibliográficos
Autor principal: Wojtak, Weronika (author)
Outros Autores: Ferreira, Flora José Rocha (author), Vicente, Paulo Sérgio Cunha (author), Louro, Luís (author), Bicho, Estela (author), Erlhagen, Wolfram (author)
Formato: article
Idioma:eng
Publicado em: 2020
Assuntos:
Value-based decision making
Action planning
Dynamic field theory
Sevice robotics
Learning
Dynamic Neural Field
Neural integrator
Assembly robot
Sequence learning
Ciências Naturais::Matemáticas
Science & Technology
Texto completo:http://hdl.handle.net/1822/69412
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/69412

Texto Completo

http://hdl.handle.net/1822/69412

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