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

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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Bibliographic Details
Main Authors: Shangding Gu, Alap Kshirsagar, Yali Du, Guang Chen, Jan Peters, Alois Knoll
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-11-01
Series:Frontiers in Neurorobotics
Subjects:
interactive behaviors
safe exploration
value alignment
safe collaboration
bi-direction information
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2023.1280341/full

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https://www.frontiersin.org/articles/10.3389/fnbot.2023.1280341/full

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