A human-centered safe robot reinforcement learning framework with interactive behaviors

Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment. Safe Robot RL (SRRL) is a crucial step toward achieving human-robot coexistence. In this paper, we envision a human-centered SRRL framework...

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Detalles Bibliográficos
Autores principales: Gu, Shangding, Kshirsagar, Alap, Du, Yali, Chen, Guang, Peters, Jan, Knoll, Alois
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665848/
https://www.ncbi.nlm.nih.gov/pubmed/38023448
http://dx.doi.org/10.3389/fnbot.2023.1280341

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665848/
https://www.ncbi.nlm.nih.gov/pubmed/38023448
http://dx.doi.org/10.3389/fnbot.2023.1280341

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