Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/69412
Título: | A neural integrator model for planning and value-based decision making of a robotics assistant |
Autor(es): | Wojtak, Weronika Ferreira, Flora José Rocha Vicente, Paulo Sérgio Cunha Louro, Luís Bicho, Estela Erlhagen, Wolfram |
Palavras-chave: | Value-based decision making Action planning Dynamic field theory Sevice robotics Learning Dynamic Neural Field Neural integrator Assembly robot Sequence learning |
Data: | 2020 |
Editora: | Springer Nature |
Revista: | Neural Computing and Applications |
Resumo(s): | 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. Here, we present an approach based on Dynamic Neural Fields that apply brain-like computations to endow a robot with these cognitive functions. A neural integrator is used to model the gradual accumulation of sensory and other evidence as time-varying persistent activity of neural populations. The decision to act is modeled by a competitive dynamics between neural populations linked to different motor behaviors. They receive the persistent activation pattern of the integrators as input. In the first experiment, a robot learns rapidly by observation the sequential order of object transfers between an assistant and an operator to subsequently substitute the assistant in the joint task. The results show that the robot is able to proactively plan the series of handovers in the correct order. In the second experiment, a mobile robot searches at two different workbenches for a specific object to deliver it to an operator. The object may appear at the two locations in a certain time period with independent probabilities unknown to the robot. The trial-by-trial decision under uncertainty is biased by the accumulated evidence of past successes and choices. The choice behavior over a longer period reveals that the robot achieves a high search efficiency in stationary as well as dynamic environments. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/69412 |
DOI: | 10.1007/s00521-020-05224-8 |
ISSN: | 0941-0643 |
Versão da editora: | http://link.springer.com/article/10.1007/s00521-020-05224-8 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
NCA_Wojtak_06_2020.pdf | 847,86 kB | Adobe PDF | Ver/Abrir |