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Autonomous Robots
Erschienen in: Autonomous Robots 5/2018

23.11.2017

Hierarchical emotional episodic memory for social human robot collaboration

verfasst von: Won-Hyong Lee, Jong-Hwan Kim

Erschienen in: Autonomous Robots | Ausgabe 5/2018

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Abstract

For social human robot collaboration, robots need to effectively remember human experiences and manage emotional experiences as well as repetitive experiences. To implement these functions, the hierarchical emotional episodic memory, using deep adaptive resonance theory network, is proposed in this paper. The proposed memory not only learns emotional experiences, but also has the ability to anticipate future emotional situations. Two parameter modulation processes, delayed consolidation and instant update, are provided. These make emotional experiences reinforce faster, remain for longer, and become more stable and sensitive to analogous experiences. Simulation analysis is conducted to verify the proposed memory, and an experiment is carried out in a kitchen environment to demonstrate social human robot collaboration.
Vorheriger Artikel Learning proactive behavior for interactive social robots
Nächster Artikel Efficient behavior learning in human–robot collaboration

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Metadaten
Titel
Hierarchical emotional episodic memory for social human robot collaboration
verfasst von
Won-Hyong Lee
Jong-Hwan Kim
Publikationsdatum
23.11.2017
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 5/2018
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-017-9679-0

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